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1.  Prevalence of thinness in children and adolescents in the Seychelles: comparison of two international growth references 
Nutrition Journal  2011;10:65.
Thinness in children and adolescents is largely under studied, a contrast with abundant literature on under-nutrition in infants and on overweight in children and adolescents. The aim of this study is to compare the prevalence of thinness using two recently developed growth references, among children and adolescents living in the Seychelles, an economically rapidly developing country in the African region.
Weight and height were measured every year in all children of 4 grades (age range: 5 to 16 years) of all schools in the Seychelles as part of a routine school-based surveillance program. In this study we used data collected in 16,672 boys and 16,668 girls examined from 1998 to 2004. Thinness was estimated according to two growth references: i) an international survey (IS), defining three grades of thinness corresponding to a BMI of 18.5, 17.0 and 16.0 kg/m2 at age 18 and ii) the WHO reference, defined here as three categories of thinness (-1, -2 and -3 SD of BMI for age) with the second and third named "thinness" and "severe thinness", respectively.
The prevalence of thinness was 21.4%, 6.4% and 2.0% based on the three IS cut-offs and 27.7%, 6.7% and 1.2% based on the WHO cut-offs. The prevalence of thinness categories tended to decrease according to age for both sexes for the IS reference and among girls for the WHO reference.
The prevalence of the first category of thinness was larger with the WHO cut-offs than with the IS cut-offs while the prevalence of thinness of "grade 2" and thinness of "grade 3" (IS cut-offs) was similar to the prevalence of "thinness" and "severe thinness" (WHO cut-offs), respectively.
PMCID: PMC3121668  PMID: 21658236
2.  Establishing a standard definition for child overweight and obesity worldwide: international survey 
BMJ : British Medical Journal  2000;320(7244):1240.
To develop an internationally acceptable definition of child overweight and obesity, specifying the measurement, the reference population, and the age and sex specific cut off points.
International survey of six large nationally representative cross sectional growth studies.
Brazil, Great Britain, Hong Kong, the Netherlands, Singapore, and the United States.
97 876 males and 94 851 females from birth to 25 years of age.
Main outcome measure
Body mass index (weight/height2).
For each of the surveys, centile curves were drawn that at age 18 years passed through the widely used cut off points of 25 and 30 kg/m2 for adult overweight and obesity. The resulting curves were averaged to provide age and sex specific cut off points from 2-18 years.
The proposed cut off points, which are less arbitrary and more internationally based than current alternatives, should help to provide internationally comparable prevalence rates of overweight and obesity in children.
PMCID: PMC27365  PMID: 10797032
3.  Appropriate Body Mass Index Cut-Offs to Determine Thinness, Overweight and Obesity in South Asian Children in The Netherlands 
PLoS ONE  2013;8(12):e82822.
Asian populations have an increased risk of developing cardiometabolic disorders at a lower body mass index (BMI) than other ethnic groups. Therefore, lower adult BMI cut-offs to determine overweight and obesity are recommended to assess the associated health risks for Asian (23 and 27.5 kg/m2 respectively) and Asian Indian (23, 25 kg/m2) populations. The objective of this study was to develop BMI cut-offs for thinness, overweight, and obesity for South Asian children in the Netherlands, and to compare the BMI cut-offs and distribution with an Asian Indian reference, the WHO Child Growth Reference, and universal BMI cut-offs.
A reference cohort of 546 Surinamese South Asian boys and 521 girls, born between 1974–1976 (during the pre-obesity era) with 3408 and 3267 BMI measurements respectively, was retrospectively analysed. BMI-for-age charts were created with the LMS method. BMI centile curves passing through the cut-off points of 15 (thinness), 23 (overweight), 25 and 27.5 kg/m2 (obesity) at 18y were drawn as cut-off levels.
The BMI of Surinamese South Asian children had a similar distribution to the Asian Indian reference, apart from a lower mean and less variation. The BMI distribution differed considerably from the WHO reference and universal BMI criteria. The calculated BMI cut-offs corresponding to a BMI of 15, 23, 25, and 27.5 kg/m2 at 18y were at the 7.1, 81.1, 89.8, and 95.5 percentile respectively in boys, and at the 2.7, 79.5, 89.2, and 95.2 percentile in girls.
This is the first study proposing BMI cut-offs for South Asian children based on measurements from a prosperous population unaffected by the obesity epidemic. We recommend the use of these cut-offs in South Asian children in the Netherlands as these better reflect the health risks associated with thinness, overweight and obesity, and therefore may prevent the development of cardiometabolic disorders.
PMCID: PMC3868582  PMID: 24367559
4.  First growth curves based on the World Health Organization reference in a Nationally-Representative Sample of Pediatric Population in the Middle East and North Africa (MENA): the CASPIAN-III study 
BMC Pediatrics  2012;12:149.
The World Health Organization (WHO) is in the process of establishing a new global database on the growth of school children and adolescents. Limited national data exist from Asian children, notably those living in the Middle East and North Africa (MENA). This study aimed to generate the growth chart of a nationally representative sample of Iranian children aged 10–19 years, and to explore how well these anthropometric data match with international growth references.
In this nationwide study, the anthropometric data were recorded from Iranian students, aged 10–19 years, who were selected by multistage random cluster sampling from urban and rural areas. Prior to the analysis, outliers were excluded from the features height-for-age and body mass index (BMI)-for-age using the NCHS/WHO cut-offs. The Box-Cox power exponential (BCPE) method was used to calculate height-for-age and BMI-for-age Z-scores for our study participants. Then, children with overweight, obesity, thinness, and severe thinness were identified using the BMI-for-age z-scores. Moreover, stunted children were detected using the height-for-age z-scores. The growth curve of the Iranian children was then generated from the z-scores, smoothed by cubic S-plines.
The study population comprised 5430 school students consisting of 2312 (44%) participants aged 10–14 years , and 3118 (58%) with 15–19 years of age. Eight percent of the participants had low BMI (thinness: 6% and severe thinness: 2%), 20% had high BMI (overweight: 14% and obesity: 6%), and 7% were stunted. The prevalence rates of low and high BMI were greater in boys than in girls (P < 0.001). The mean BMI-for-age, and the average height-for-age of Iranian children aged 10–19 years were lower than the WHO 2007 and United states Centers for Disease Control and Prevention 2000 (USCDC2000) references.
The current growth curves generated from a national dataset may be included for establishing WHO global database on children’s growth. Similar to most low-and middle income populations, Iranian children aged 10–19 years are facing a double burden of weight disorders, notably under- and over- nutrition, which should be considered in public health policy-making.
PMCID: PMC3471000  PMID: 22985219
Growth; Iran; Reference curve; Weight disorder
5.  Weight status among Iranian adolescents: Comparison of four different criteria 
Obesity or being overweight is a major health problem in Iran. Only few studies are available that compare the obesity prevalence by four different available criteria. The aim of this study was to determine the prevalence of overweight and obesity among Isfahani adolescents based on four different definitions.
Materials and Methods:
This cross-sectional study was conducted on 3002 Isfahani students (1377 males; 1625 females) aged 11-18 years. Anthropometric measurements including weight and height were measured and body mass index (BMI) was calculated. Sex-specific BMI-for-age reference data of the Iranian national data, Center for Disease Control data (CDC2000), International Obesity taskforce data (IOTF), and recent World Health Organization (WHO) data was used to define overweight and obesity.
The mean age of the studied population was 14.8 years and the mean BMI was 20.3 kg/m2. Girls were on an average 1.4 years older and had almost one unit higher BMI than boys. Underweight was prevalent among almost 38.5% and 25.5% of adolescents as per WHO2007 and national Iranian cut-off points, respectively. The prevalence rates reached 39.5% and 45.8% by IOTF and CDC2000 criteria, respectively. The highest prevalence of overweight was obtained by IOTF cut-points (30.5%), while CDC2000 criteria, WHO2007, and national Iranian cut-points gave similar prevalence results (4.7%, 4.0%, and 4.4%); 2.4% of the studied population were found to be obese by WHO2007 definition, while this rate was 0.8%, 0.5%, and 0.8% by IOTF, CDC2000, and national Iranian cut-points.
Almost all definitions revealed coexistence of underweight, overweight, and obesity among Isfahani adolescents. Huge differences exist between different criteria for assessing weight status among children. To understand the best appropriate criteria for Iranian adolescents, future studies should focus on the predictability of obesity related co-morbidities by these criteria.
PMCID: PMC3872601  PMID: 24379838
Adolescents; body mass index; obesity; overweight; prevalence; weight
6.  Height, weight and BMI percentiles and nutritional status relative to the international growth references among Pakistani school-aged children 
BMC Pediatrics  2012;12:31.
Child growth is internationally recognized as an important indicator of nutritional status and health in populations. This study was aimed to compare age- and gender-specific height, weight and BMI percentiles and nutritional status relative to the international growth references among Pakistani school-aged children.
A population-based study was conducted with a multistage cluster sample of 1860 children aged five to twelve years in Lahore, Pakistan. Smoothed height, weight and BMI percentile curves were obtained and comparison was made with the World Health Organization 2007 (WHO) and United States' Centers for Disease Control and Prevention 2000 (USCDC) references. Over- and under-nutrition were defined according to the WHO and USCDC references, and the International Obesity Task Force (IOTF) cut-offs. Simple descriptive statistics were used and statistical significance was considered at P < 0.05.
Height, weight and BMI percentiles increased with age among both boys and girls, and both had approximately the same height and a lower weight and BMI as compared to the WHO and USCDC references. Mean differences from zero for height-, weight- and BMI-for-age z score values relative to the WHO and USCDC references were significant (P < 0.001). Means of height-for-age (present study: 0.00, WHO: -0.19, USCDC: -0.24), weight-for-age (present study: 0.00, WHO: -0.22, USCDC: -0.48) and BMI-for-age (present study: 0.00, WHO: -0.32, USCDC: -0.53) z score values relative to the WHO reference were closer to zero and the present study as compared to the USCDC reference. Mean differences between weight-for-age (0.19, 95% CI 0.10-0.30) and BMI-for-age (0.21, 95% CI 0.11-0.30) z scores relative to the WHO and USCDC references were significant. Over-nutrition estimates were higher (P < 0.001) by the WHO reference as compared to the USCDC reference (17% vs. 15% overweight and 7.5% vs. 4% obesity) while underweight and thinness/wasting were lower (P < 0.001) by the WHO reference as compared to the USCDC reference (7% vs. 12% underweight and 10% vs. 13% thinness). Significantly lower overweight (8%) and obesity (5%) prevalence and higher thinness grade one prevalence (19%) was seen with use of the IOTF cut-offs as compared to the WHO and USCDC references. Mean difference between height-for-age z scores and difference in stunting prevalence relative to the WHO and USCDC references was not significant.
Pakistani school-aged children significantly differed from the WHO and USCDC references. However, z score means relative to the WHO reference were closer to zero and the present study as compared to the USCDC reference. Overweight and obesity were significantly higher while underweight and thinness/wasting were significantly lower relative to the WHO reference as compared to the USCDC reference and the IOTF cut-offs. New growth charts for Pakistani children based on a nationally representative sample should be developed. Nevertheless, shifting to use of the 2007 WHO child growth reference might have important implications for child health programs and primary care pediatric clinics.
PMCID: PMC3337223  PMID: 22429910
7.  Glycolipid metabolic status of overweight/obese adolescents aged 9- to 15-year-old and the BMI-SDS/BMI cut-off value of predicting dyslipidemiain boys, Shanghai, China: a cross-sectional study 
The prevalence of adolescents’ obesity and overweight has dramatically elevated in China. Obese children were likely to insulin resistance and dyslipidemia, which are risk factors of cardiovascular diseases. However there was no cut-off point of anthropometric values to predict the risk factors in Chinese adolescents. The present study was to investigate glycolipid metabolism status of adolescents in Shanghai and to explore the correlations between body mass index standard deviation score (BMI-SDS) and metabolic indices, determine the best cut-off value of BMI-SDS to predict dyslipidemia.
Fifteen schools in Shanghai’s two districts were chosen by cluster sampling and primary screening was done in children aged 9-15 years old. After screening of bodyweight and height, overweight and obese adolescents and age-matched children with normal body weight were randomly recruited in the study. Anthropometric measurements, biochemical measurements of glycolipid profiles were done. SPSS19.0 was used to analyze the data. Receiver operating characteristic (ROC) curves were made and the best cut-off values of BMI-SDS to predict dyslipidemia were determined while the Youden indices were maximum.
Five hundred and thirty-eight adolescents were enrolled in this research, among which 283 have normal bodyweight, 115 were overweight and 140 were obese. No significant differences of the ages among 3 groups were found. There were significant differences of WC-SDS (p<0.001), triacylglycerol (p<0.05), high and low density lipoprotein cholesterol (p<0.01), fasting insulin (p<0.01) and C-peptide (p<0.001) among 3 groups. Significant difference of fasting glucose was only found between normal weight and overweight group. Significant difference of total cholesterol was found between obese and normal weight group. There was no significant difference of glycated hemoglobin among 3 groups. The same tendency was found in boys but not in girls. Only HDL-C reduced and TG increased while BMI elevated in girls. The best cut-off value of BMI-SDS was 1.22 to predict dyslipidemia in boys. The BMI cut-off was 21.67 in boys.
Overweight and obese youths had reduced insulin sensitivity and high prevalence of dyslipidemia.When BMI-SDS elevated up to 1.22 and BMI was higher than 21.67 in boys, dyslipidemia may happen.
PMCID: PMC3766195  PMID: 23984682
Adolescents; Children; Lipid metabolism; Obesity; Overweight; BMI-SDS; China
8.  Body Mass Index Reference Curves for Children Aged 0-18 Years in Shaanxi, China 
Health care professionals have recommended the use of age-related body mass index (BMI) to evaluate obesity in children. Until now, no age-related reference curves for BMI have been reported in China. Presented here are age-related BMI percentile curves for children aged 0~18 years in Shaanxi, China, 1995.
The Third Nationwide Growth Survey was performed in 1995 and from this survey, data of the Shaanxi population were retrieved to construct the age-related BMI percentile curves. A total of 27,200 healthy children aged 0~18 years were examined for height and weight, using the standardized methods. The λ-median-coefficient of variation (LMS) method was used for curve fitting; all analyses were carried out on the basis of different sexes and areas through a special program for LMS method.
Median BMI increased steeply in early life, with a peak at 8 months, then declined, and then leveled off at about 6 years. The age of adiposity rebound for urban children was about two years earlier than that for rural children and one year earlier for boys than for girls. After adiposity rebound, BMI increased more rapidly in girls than in boys, and the increase in urban children was more rapid than that in rural children. As the onset of puberty, female BMI became higher than that of males, and the difference between boys and girls was larger for rural children than for urban children. The 95th, 50th and 5th percentiles for Shaanxi children were lower than those of comparable American children. Cut-off points for obesity was lower than those of international averages, suggesting the nutrition status of Shaanxi children is lower than that of children in developed countries, and has not reached the international average level.
Using the LMS method, we constructed age-related BMI percentile curves for Shaanxi children aged 0~18 years, the first for Chinese children. Percentile curves and cut-off points for obesity can be used as a reference for assessing the nutrition status of Shaanxi children aged 0~18 years. The identified gender and residency differences may serve as guides to an understanding of the cause and prevention of obesity.
PMCID: PMC3614580  PMID: 23674955
body mass index; growth reference; obesity; Chinese children
9.  Change in the Body Mass Index Distribution for Women: Analysis of Surveys from 37 Low- and Middle-Income Countries 
PLoS Medicine  2013;10(1):e1001367.
Using cross-sectional surveys, Fahad Razak and colleagues investigate how the BMI (body mass index) distribution is changing for women in low- and middle-income countries.
There are well-documented global increases in mean body mass index (BMI) and prevalence of overweight (BMI≥25.0 kg/m2) and obese (BMI≥30.0 kg/m2). Previous analyses, however, have failed to report whether this weight gain is shared equally across the population. We examined the change in BMI across all segments of the BMI distribution in a wide range of countries, and assessed whether the BMI distribution is changing between cross-sectional surveys conducted at different time points.
Methods and Findings
We used nationally representative surveys of women between 1991–2008, in 37 low- and middle-income countries from the Demographic Health Surveys ([DHS] n = 732,784). There were a total of 96 country-survey cycles, and the number of survey cycles per country varied between two (21/37) and five (1/37). Using multilevel regression models, between countries and within countries over survey cycles, the change in mean BMI was used to predict the standard deviation of BMI, the prevalence of underweight, overweight, and obese. Changes in median BMI were used to predict the 5th and 95th percentile of the BMI distribution. Quantile-quantile plots were used to examine the change in the BMI distribution between surveys conducted at different times within countries. At the population level, increasing mean BMI is related to increasing standard deviation of BMI, with the BMI at the 95th percentile rising at approximately 2.5 times the rate of the 5th percentile. Similarly, there is an approximately 60% excess increase in prevalence of overweight and 40% excess in obese, relative to the decline in prevalence of underweight. Quantile-quantile plots demonstrate a consistent pattern of unequal weight gain across percentiles of the BMI distribution as mean BMI increases, with increased weight gain at high percentiles of the BMI distribution and little change at low percentiles. Major limitations of these results are that repeated population surveys cannot examine weight gain within an individual over time, most of the countries only had data from two surveys and the study sample only contains women in low- and middle-income countries, potentially limiting generalizability of findings.
Mean changes in BMI, or in single parameters such as percent overweight, do not capture the divergence in the degree of weight gain occurring between BMI at low and high percentiles. Population weight gain is occurring disproportionately among groups with already high baseline BMI levels. Studies that characterize population change should examine patterns of change across the entire distribution and not just average trends or single parameters.
Please see later in the article for the Editors' Summary
Editors' Summary
The number of obese people (individuals who have an excessive amount of body fat) is rapidly increasing in many countries. Globally, there were about 200 million obese adults in 1995; by 2010, 475 million adults were obese and another billion were classified as overweight. Obesity is defined as having a body mass index (BMI, an indicator of body fat calculated by dividing a person's weight in kilograms by their height in meters squared) of more than 30.0 kg/m2. Compared to people with a healthy weight (a BMI between 18.5 and 24.9 kg/m2), obese individuals and overweight individuals (who have a BMI between 25.0 and 29.9 kg/m2) have an increased risk of developing diabetes, heart disease and stroke, and tend to die younger. At the same time in many developing countries substantial numbers of people are underweight (BMI <18.5 kg/m2) or have chronic energy deficiency (BMI <16.0 kg/m2) and are at risk of increased risk of dying due to infectious disease or respiratory problems.
Why Was This Study Done?
The global obesity epidemic is usually described in terms of increases in the average BMI or in the prevalence of obesity (the proportion of the population whose BMI is above 30.0 kg/m2). Such descriptions assume that the BMIs of fat and thin people are increasing at the same rate and that the shape of the population's BMI distribution curve remains constant. However, as average BMI and the prevalence of obesity can increase it is unclear how the prevalence of underweight changes. This is potentially important for the health of the population because underweight individuals, like obese individuals, tend to die younger than healthy weight individuals, particularly in low-income countries. In this study, the researchers use repeated cross-sectional survey data collected from low- and middle-income countries in the Demographic and Health Surveys (DHS) to examine changes in BMI in women across the BMI distribution between 1991 and 2008. Repeated cross-sectional surveys collect data from a population at multiple time points from different individuals drawn from the same population, DHS are a data collection and surveillance project that help developing countries track health and population trends.
What Did the Researchers Do and Find?
The researchers used statistical models to analyze data from DHS surveys of more than 730,000 women living in 37 low- and middle-income countries (two to five surveys per country). Increasing average BMI was associated with an increase in the standard deviation of BMI (a measure of the dispersion of BMI in the population) both across and within countries over time. With increasing average BMI, the BMI at both the 5th and 95th percentile increased; 90% of the BMIs in a population lie between these percentiles so these BMI values indicate the spread of the BMI distribution. However, the BMI at the 95th percentile increased about 2.5 times faster than the BMI at the 5th percentile. Moreover, with increasing average BMI, the prevalence of overweight and obesity increased faster than the decline in the prevalence of underweight. Finally, quantile-quantile plots for each country (a graphical method that compares two distributions) revealed a consistent pattern of unequal weight gain across the BMI distribution as average BMI increased, with pronounced weight gains at the obese end of the distribution and little change at the underweight end.
What Do These Findings Mean?
These findings show that increases in average BMI are associated with an increased spread of BMI across and within populations. Consequently, changes in average BMI or single measurements such as the prevalence of overweight do not capture the divergence in the degree of weight gain occurring between that part of the population that has a low BMI and that part that has a high BMI. In other words, at least for the low- and middle-income countries included in this study, population weight gain is occurring disproportionately among groups with high baseline BMI levels. The researchers suggest, therefore, that the characterization of the BMI of populations over time should examine the patterns of change across the whole BMI distribution. Moreover, rather than a single broad population strategy for weight control, optimum health outcomes, they suggest, might be achieved by a strategy that includes targeted interventions to reduce weight in high BMI segments of the population and to increase weight in low BMI segments.
Additional Information
Please access these Web sites via the online version of this summary at
The US Centers for Disease Control and Prevention provides information on all aspects of overweight and obesity (in English and Spanish)
The World Health Organization provides information on obesity (in several languages); Malri's story describes the health risks faced by an obese child
The UK National Health Service Choices website also provides detailed information about obesity and a link to a personal story about losing weight
The International Obesity Taskforce provides information about the global obesity epidemic
The US Department of Agriculture's website provides a personal healthy eating plan; the Weight-control Information Network is an information service provided for the general public and health professionals by the US National Institute of Diabetes and Digestive and Kidney Diseases (in English and Spanish)
MedlinePlus has links to further information about obesity (in English and Spanish)
PMCID: PMC3545870  PMID: 23335861
10.  Genetic Markers of Adult Obesity Risk Are Associated with Greater Early Infancy Weight Gain and Growth 
PLoS Medicine  2010;7(5):e1000284.
Ken Ong and colleagues genotyped children from the ALSPAC birth cohort and showed an association between greater early infancy gains in weight and length and genetic markers for adult obesity risk.
Genome-wide studies have identified several common genetic variants that are robustly associated with adult obesity risk. Exploration of these genotype associations in children may provide insights into the timing of weight changes leading to adult obesity.
Methods and Findings
Children from the Avon Longitudinal Study of Parents and Children (ALSPAC) birth cohort were genotyped for ten genetic variants previously associated with adult BMI. Eight variants that showed individual associations with childhood BMI (in/near: FTO, MC4R, TMEM18, GNPDA2, KCTD15, NEGR1, BDNF, and ETV5) were used to derive an “obesity-risk-allele score” comprising the total number of risk alleles (range: 2–15 alleles) in each child with complete genotype data (n = 7,146). Repeated measurements of weight, length/height, and body mass index from birth to age 11 years were expressed as standard deviation scores (SDS). Early infancy was defined as birth to age 6 weeks, and early infancy failure to thrive was defined as weight gain between below the 5th centile, adjusted for birth weight. The obesity-risk-allele score showed little association with birth weight (regression coefficient: 0.01 SDS per allele; 95% CI 0.00–0.02), but had an apparently much larger positive effect on early infancy weight gain (0.119 SDS/allele/year; 0.023–0.216) than on subsequent childhood weight gain (0.004 SDS/allele/year; 0.004–0.005). The obesity-risk-allele score was also positively associated with early infancy length gain (0.158 SDS/allele/year; 0.032–0.284) and with reduced risk of early infancy failure to thrive (odds ratio  = 0.92 per allele; 0.86–0.98; p = 0.009).
The use of robust genetic markers identified greater early infancy gains in weight and length as being on the pathway to adult obesity risk in a contemporary birth cohort.
Please see later in the article for the Editors' Summary
Editors' Summary
The proportion of overweight and obese children is increasing across the globe. In the US, the Surgeon General estimates that, compared with 1980, twice as many children and three times the number of adolescents are now overweight. Worldwide, 22 million children under five years old are considered by the World Health Organization to be overweight.
Being overweight or obese in childhood is associated with poor physical and mental health. In addition, childhood obesity is considered a major risk factor for adult obesity, which is itself a major risk factor for cancer, heart disease, diabetes, osteoarthritis, and other chronic conditions.
The most commonly used measure of whether an adult is a healthy weight is body mass index (BMI), defined as weight in kilograms/(height in metres)2. However, adult categories of obese (>30) and overweight (>25) BMI are not directly applicable to children, whose BMI naturally varies as they grow. BMI can be used to screen children for being overweight and or obese but a diagnosis requires further information.
Why Was This Study Done?
As the numbers of obese and overweight children increase, a corresponding rise in future numbers of overweight and obese adults is also expected. This in turn is expected to lead to an increasing incidence of poor health. As a result, there is great interest among health professionals in possible pathways between childhood and adult obesity. It has been proposed that certain periods in childhood may be critical for the development of obesity.
In the last few years, ten genetic variants have been found to be more common in overweight or obese adults. Eight of these have also been linked to childhood BMI and/or obesity. The authors wanted to identify the timing of childhood weight changes that may be associated with adult obesity. Knowledge of obesity risk genetic variants gave them an opportunity to do so now, without following a set of children to adulthood.
What Did the Researchers Do and Find?
The authors analysed data gathered from a subset of 7,146 singleton white European children enrolled in the Avon Longitudinal Study of Parents and Children (ALSPAC) study, which is investigating associations between genetics, lifestyle, and health outcomes for a group of children in Bristol whose due date of birth fell between April 1991 and December 1992. They used knowledge of the children's genetic makeup to find associations between an obesity risk allele score—a measure of how many of the obesity risk genetic variants a child possessed—and the children's weight, height, BMI, levels of body fat (at nine years old), and rate of weight gain, up to age 11 years.
They found that, at birth, children with a higher obesity risk allele score were not any heavier, but in the immediate postnatal period they were less likely to be in the bottom 5% of the population for weight gain (adjusted for birthweight), often termed “failure to thrive.” At six weeks of age, children with a higher obesity risk allele score tended to be longer and heavier, even allowing for weight at birth.
After six weeks of age, the obesity risk allele score was not associated with any further increase in length/height, but it was associated with a more rapid weight gain between birth and age 11 years. BMI is derived from height and weight measurements, and the association between the obesity risk allele score and BMI was weak between birth and age three-and-a-half years, but after that age the association with BMI increased rapidly. By age nine, children with a higher obesity risk allele score tended to be heavier and taller, with more fat on their bodies.
What Do These Findings Mean?
The combined obesity allele risk score is associated with higher rates of weight gain and adult obesity, and so the authors conclude that weight gain and growth even in the first few weeks after birth may be the beginning of a pathway of greater adult obesity risk.
A study that tracks a population over time can find associations but it cannot show cause and effect. In addition, only a relatively small proportion (1.7%) of the variation in BMI at nine years of age is explained by the obesity risk allele score.
The authors' method of finding associations between childhood events and adult outcomes via genetic markers of risk of disease as an adult has a significant advantage: the authors did not have to follow the children themselves to adulthood, so their findings are more likely to be relevant to current populations. Despite this, this research does not yield advice for parents how to reduce their children's obesity risk. It does suggest that “failure to thrive” in the first six weeks of life is not simply due to a lack of provision of food by the baby's caregiver but that genetic factors also contribute to early weight gain and growth.
The study looked at the combined obesity risk allele score and the authors did not attempt to identify which individual alleles have greater or weaker associations with weight gain and overweight or obesity. This would require further research based on far larger numbers of babies and children. The findings may also not be relevant to children in other types of setting because of the effects of different nutrition and lifestyles.
Additional Information
Please access these Web sites via the online version of this summary at
Further information is available on the ALSPAC study
The UK National Health Service and other partners provide guidance on establishing a healthy lifestyle for children and families in their Change4Life programme
The International Obesity Taskforce is a global network of expertise and the advocacy arm of the International Association for the Study of Obesity. It works with the World Health Organization, other NGOs, and stakeholders and provides information on overweight and obesity
The Centers for Disease Control and Prevention (CDC) in the US provide guidance and tips on maintaining a healthy weight, including BMI calculators in both metric and Imperial measurements for both adults and children. They also provide BMI growth charts for boys and girls showing how healthy ranges vary for each sex at with age
The Royal College of Paediatrics and Child Health provides growth charts for weight and length/height from birth to age 4 years that are based on WHO 2006 growth standards and have been adapted for use in the UK
The CDC Web site provides information on overweight and obesity in adults and children, including definitions, causes, and data
The CDC also provide information on the role of genes in causing obesity.
The World Health Organization publishes a fact sheet on obesity, overweight and weight management, including links to childhood overweight and obesity
Wikipedia includes an article on childhood obesity (note that Wikipedia is a free online encyclopedia that anyone can edit; available in several languages)
PMCID: PMC2876048  PMID: 20520848
11.  The association of self-esteem, depression and body satisfaction with obesity among Turkish adolescents 
BMC Public Health  2007;7:80.
The purpose of this study was to determine the prevalence of overweight and obesity and to examine the effects of actual weight status, perceived weight status and body satisfaction on self-esteem and depression in a high school population in Turkey.
A cross-sectional survey of 2101 tenth-grade Turkish adolescents aged 15–18 was conducted. Body mass index (BMI) was calculated using weight and height measures. The overweight and obesity were based on the age- and gender-spesific BMI cut-off points of the International Obesity Task Force values. Self-esteem was measured using the Rosenberg Self-Esteem Scale, and depression was measured using Children's Depression Inventory. Logistic regression analysis was used to examine relationships among the variables.
Based on BMI cut-off points, 9.0% of the students were overweight and 1.1% were obese. Logistic regression analysis indicated that (1) being male and being from a higher socio-economical level were important in the prediction of overweight based on BMI; (2) being female and being from a higher socio-economical level were important in the prediction of perceived overweight; (3) being female was important in the prediction of body dissatisfaction; (4) body dissatisfaction was related to low self-esteem and depression, perceived overweight was related only to low self-esteem but actual overweight was not related to low self-esteem and depression in adolescents.
The results of this study suggest that school-based adolescents in urban Turkey have a lower risk of overweight and obesity than adolescents in developed countries. The findings of this study suggest that psychological well-being of adolescents is more related to body satisfaction than actual and perceived weight status is.
PMCID: PMC1888702  PMID: 17506879
12.  Underweight, Overweight and Obesity Among Zaboli Adolescents: A Comparison Between International and Iranians’ National Criteria 
Obesity and overweight are the major health problems in Iran. The aim of this study was to determine the prevalence of overweight and obesity among adolescents living in Zabol settled in Sistan va Baluchistan, one of economically underprivileged provinces in South Eastern of Iran, based on four different definitions.
This cross-sectional study was accomplished among a sample of 837 Zaboli adolescents (483 males; 354 females) aged 11-15 years. Anthropometric measurements including weight and height were measured and body mass index (BMI) was calculated. Sex-specific BMI-for-age reference data of the Iranian national data, Centers for Disease Control data (CDC 2000), International Obesity Task Force data (IOTF) and recent World Health Organization (WHO) data was used to define overweight and obesity.
Mean age of the studied population was 13.14 year. Underweight was prevalent among almost 18.7% and 18.4% of adolescents by the use of WHO 2007 and CDC 2000 cut-off points. The prevalence rates reached 25.8% and 27.2% by IOTF and Iranian national criteria, respectively. The highest prevalence of overweight was obtained by IOTF cut-points (10.8%) followed by CDC 2000 criteria (9.4%), WHO 2007 (8.8%) while national Iranian cut-points resulted in the lowest prevalence (2.4%). 7.5% of the studied population were found to be obese by WHO 2007 definition, while this rate was 2.2%, 3.4% and 1.5% by IOTF, CDC 2000 and national Iranian cut-points.
Almost all definitions revealed coexistence of underweight, overweight, and obesity among Zaboli adolescents. Huge differences exist between different criteria. To understand the best appropriate criteria for Iranian adolescents, future studies should focus on the predictability of obesity-related co-morbidities by these criteria.
PMCID: PMC3733182  PMID: 23930162
Adolescents; body mass index; Iran; obesity; overweight; prevalence; Zabol
13.  The normal range of body mass index with high body fat percentage among male residents of Lucknow city in north India 
Background & objectives:
Several studies have raised the suspicion that the body mass index (BMI) cut-off for overweight as defined by the WHO may not adequately reflect the actual overweight status. The present study looked at the relationship between BMI and body fat per cent (BF %) / health risks (hypertension and type 2 diabetes) in male residents of Lucknow city, north India to evaluate the validity of BMI cut-off points for overweight.
One thousand one hundred and eleven male volunteer subjects (18-69 yr) who participated in different programmes organized by the Institute during 2005 to 2008 were included in the study. BF% was measured using commercially available digital weight scale incorporating bioelectrical impedance (BI) analyzer. The proposed cut-off for BMI based on BF % was calculated using receiver operating characteristics (ROC) curve analysis.
Forty four per cent subjects showed higher BF % (>25%) with BMI range (24-24.99 kg/m2). Sensitivity and specificity at BMI cut-off at 24.5 kg/m3 were 83.2 and 77.5, respectively. Sensitivity at BMI cut-off >25 kg/m2 was reduced by 5 per cent and specificity increased by 4.6 per cent when compared to 24.5 cut-off.
Interpretation & conclusions:
The study subjects showed higher body fat percentage and risk factors like hypertension and type 2 diabetes at normal BMI range proposed by the WHO. The cut-off for BMI was proposed to be 24.5 kg/m2 for our study population. If overweight is regarded as an excess of body fat and not as an excess of weight (increased BMI), the cut-off points for overweight based on BMI would need to be lowered. However, the confidence of estimate of the BMI cut-off in the present study may be considered with the limitations of BI analysis studies.
PMCID: PMC3307188  PMID: 22382186
BMI; body fat %; new cut-off; overweight
14.  Defining Body Fatness in Adolescents: A Proposal of the Afad-A Classification 
PLoS ONE  2013;8(2):e55849.
Body mass index (BMI) shows several limitations as indicator of fatness. Using the International Obesity Task Force (IOTF) reference and the World Health Organization (WHO) standard 2007 on the same dataset yielded widely different rates. At higher levels, BMI and the BMI cut-offs may be help in informing a clinical judgement, but at levels near the norm additional criteria may be needed. This study compares the prevalence of overweight and obesity using IOTF and WHO-2007 references and interprets body composition by comparing measures of BMI and body fatness (fat mass index, FMI; and waist-to-height ratio, WHtR) among an adolescent population.
Methods and Results
A random sample (n = 1231) of adolescent population (12–17 years old) was interviewed. Weight, height, waist circumference, triceps and subscapular skinfolds were used to calculate BMI, FMI, and WHtR. The prevalence of overweight and obesity were 12.3% and 15.4% (WHO standards) and 18.6% and 6.1% (IOTF definition). Despite that IOTF cut-offs misclassified less often than WHO standards, BMI categories were combined with FMI and WHtR resulting in the Adiposity & Fat Distribution for adolescents (AFAD-A) classification, which identified the following groups normal-weight normal-fat (73.2%), normal-weight overfat (2.1%), overweight normal-fat (6.7%), overweight overfat (11.9%) and obesity (6.1%), and also classified overweight at risk and obese adolescents into type-I (9.5% and 1.3%, respectively) and type-II (2.3% and 4.9%, respectively) depending if they had or not abdominal fatness.
There are differences between IOTF and WHO-2007 international references and there is a misclassification when adiposity is considered. The BMI limitations, especially for overweight identification, could be reduced by adding an estimate of both adiposity (FMI) and fat distribution (WHtR). The AFAD-A classification could be useful in clinical and population health to identify overfat adolescent and those who have greater risk of developing weight-related cardiovascular diseases according to the BMI category.
PMCID: PMC3566104  PMID: 23405220
15.  Is body mass index (BMI) a useful measure of excess body fatness in adolescents and young adults with Down syndrome? 
To determine the validity of body mass index (BMI) to identify excess fatness in youth with Down syndrome (DS).
Using the CDC growth reference, we defined overweight (≥85th percentile) and obesity (≥95th percentile) based on participants’ age- and sex-specific BMI z-scores, calculated from measured height and weight. Percentage body fat (%BF) was measured by dual-energy X-ray absorptiometry. We determined sensitivity, specificity, positive predictive value, negative predictive value, and efficiency of BMI percentiles to identify excess adiposity relative to elevated %BF cut-offs developed from the Pediatric Rosetta Body Composition project (Freedman et al., 2009b) in 32 youth (20M/12F), ages 13–21 years with Down syndrome.
For adolescents with Down syndrome using the cut-off points of 95th percentile for BMI (obesity), sensitivity and specificity were 71% and 96%, respectively. Positive predictive value was 83% and negative predictive value was 92%. Overall efficiency was 91%. Sensitivity and specificity for BMI cut-offs above the 85th percentile (overweight) were 100% and 60%, respectively. The positive predictive value was 41% and negative predictive value was 100%. Overall efficiency was 69%.
On the whole, the obesity (≥95th percentile) cut-off performs better than the overweight cut-off (85th–94th percentile) in identifying elevated fatness in youth with DS.
PMCID: PMC4019440  PMID: 22974061
16.  Cut-off Values of Body Mass Index, Waist Circumference, and Waist-to-Height Ratio to Identify Excess Abdominal Fat: Population-Based Screening of Japanese Schoolchildren 
Journal of Epidemiology  2011;21(3):191-196.
School-based screening and prevention programs for adiposity generally target school children in grades 4 and 6 (age 9–11 years). The aims of this study were to evaluate the validity of body mass index (BMI), waist circumference (WC), and waist-to-height ratio (WHtR) in identifying abdominal adiposity in fifth-grade Japanese school children and to determine optimal cut-off values for anthropometric measures.
The target population was fifth-grade school children enrolled in 2 schools in Shizuoka, Japan between 2008 and 2010; 422 of the 466 children participated in the present study. Abdominal adiposity was defined as percent trunk fat in the 95th percentile or higher, as determined by dual-energy x-ray absorptiometry (DXA). We analyzed the validity of BMI, WC, and WHtR using receiver operating characteristic (ROC) curve analysis. The Youden index was used to determine cut-off values of BMI, WC, and WHtR that identify excess abdominal fat.
Optimal cut-off values to identify abdominal adiposity were 20.8 kg/m2 (BMI), 76.5 cm (WC), and 0.519 (WHtR) for boys, and 19.6 kg/m2 (BMI), 73.0 cm (WC), and 0.499 (WHtR) for girls. Areas under the ROC curve were 0.983 (BMI), 0.987 (WC), and 0.981 (WHtR) for boys, and 0.981 (BMI), 0986 (WC), and 0.992 (WHtR) for girls.
BMI, WC, and WHtR successfully identified a high proportion of children with excess abdominal fat as measured by DXA, demonstrating that these measures are useful indices for school screening.
PMCID: PMC3899408  PMID: 21467729
child; screening; obesity; statistics as topic; reference values
17.  Correction of Body-Mass Index Using Body-Shape Perception and Socioeconomic Status in Adolescent Self-Report Surveys 
PLoS ONE  2014;9(5):e96768.
To propose a simple correction of body-mass index (BMI) based on self-reported weight and height (reported BMI) using gender, body shape perception and socioeconomic status in an adolescent population.
341 boys and girls aged 17–18 years were randomly selected from a representative sample of 2165 French adolescents living in Paris surveyed in 2010. After an anonymous self-administered pen-and-paper questionnaire asking for height, weight, body shape perception (feeling too thin, about the right weight or too fat) and socioeconomic status, subjects were measured and weighed. BMI categories were computed according to Cole’s cut-offs. Reported BMIs were corrected using linear regressions and ROC analyses and checked with cross-validation and multiple imputations to handle missing values. Agreement between actual and corrected BMI values was estimated with Kappa indexes and Intraclass correlation coefficients (ICC).
On average, BMIs were underreported, especially among girls. Kappa indexes between actual and reported BMI were low, especially for girls: 0.56 95%CI = [0.42–0.70] for boys and 0.45 95%CI = [0.30–0.60] for girls. The regression of reported BMI by gender and body shape perception gave the most balanced results for both genders: the Kappa and ICC obtained were 0.63 95%CI = [0.50–0.76] and 0.67, 95%CI = [0.58–0.74] for boys; 0.65 95%CI = [0.52–0.78] and 0.74, 95%CI = [0.66–0.81] for girls. The regression of reported BMI by gender and socioeconomic status led to similar corrections while the ROC analyses were inaccurate.
Using body shape perception, or socioeconomic status and gender is a promising way of correcting BMI in self-administered questionnaires, especially for girls.
PMCID: PMC4028195  PMID: 24844229
18.  Is waist-to-height ratio a useful indicator of cardio-metabolic risk in 6-10-year-old children? 
BMC Pediatrics  2013;13:91.
Childhood obesity is a public health problem worldwide. Visceral obesity, particularly associated with cardio-metabolic risk, has been assessed by body mass index (BMI) and waist circumference, but both methods use sex-and age-specific percentile tables and are influenced by sexual maturity. Waist-to-height ratio (WHtR) is easier to obtain, does not involve tables and can be used to diagnose visceral obesity, even in normal-weight individuals. This study aims to compare the WHtR to the 2007 World Health Organization (WHO) reference for BMI in screening for the presence of cardio-metabolic and inflammatory risk factors in 6–10-year-old children.
A cross-sectional study was undertaken with 175 subjects selected from the Reference Center for the Treatment of Children and Adolescents in Campos, Rio de Janeiro, Brazil. The subjects were classified according to the 2007 WHO standard as normal-weight (BMI z score > −1 and < 1) or overweight/obese (BMI z score ≥ 1). Systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting glycemia, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglyceride (TG), Homeostatic Model Assessment – Insulin Resistance (HOMA-IR), leukocyte count and ultrasensitive C-reactive protein (CRP) were also analyzed.
There were significant correlations between WHtR and BMI z score (r = 0.88, p < 0.0001), SBP (r = 0.51, p < 0.0001), DBP (r = 0.49, p < 0.0001), LDL (r = 0.25, p < 0.0008, HDL (r = −0.28, p < 0.0002), TG (r = 0.26, p < 0.0006), HOMA-IR (r = 0.83, p < 0.0001) and CRP (r = 0.51, p < 0.0001). WHtR and BMI areas under the curve were similar for all the cardio-metabolic parameters. A WHtR cut-off value of > 0.47 was sensitive for screening insulin resistance and any one of the cardio-metabolic parameters.
The WHtR was as sensitive as the 2007 WHO BMI in screening for metabolic risk factors in 6-10-year-old children. The public health message “keep your waist to less than half your height” can be effective in reducing cardio-metabolic risk because most of these risk factors are already present at a cut point of WHtR ≥ 0.5. However, as this is the first study to correlate the WHtR with inflammatory markers, we recommend further exploration of the use of WHtR in this age group and other population-based samples.
PMCID: PMC3686671  PMID: 23758779
Waist-to-height ratio; Obesity; Insulin resistance; Cardiovascular disease; Body mass index
19.  Defining overweight and obesity among Greek children living in Thessaloniki: International versus local reference standards 
Hippokratia  2011;15(2):141-146.
Background: Body Mass Index (BMI) offers a simple and reasonable measure of obesity that, with the use of the appropriate reference, can help in the early detection of children with weight problems. Our aim was to compare the two most commonly used international BMI references and the national Greek BMI reference in identifying Greek children being overweight and obese.
Methods: A group of 1557 children (820 girls and 737 boys, mean age: 11.42 ± 3.51 years) were studied. Weight and height was measured using standard methods, and BMI was calculated. Overweight and obesity were determined using the International Obesity Task Force (IOTF) standards, the Centers for Disease Control and Prevention (CDC) BMI-forage curves and the most recent Greek BMI-for-age curves.
Results: Results showed that the IOTF's cut-off limits identifies a significantly higher prevalence of overweight (22.4%) compared with both the CDC's (11.8%, p=0.03) and the Greek's (7.4%, p=0.002) cut-off limits. However, the prevalence of obesity was generally increased when it was determined using the CDC's cut-off limits (13.9%) compared to the prevalence calculated with both the IOTF's (6.5%, p=0.05) and the Greek's (6.9%, n.s.) cut off limits.
Conclusions: The use of the national Greek reference standards for BMI underestimates the true prevalence of overweight and obesity. On the contrary, both the IOTF and the CDC standards, although independently, detect an increased number of overweight and obese children and thus they should be adopted in the clinical practice for an earlier identification and a timelier intervention.
PMCID: PMC3209677  PMID: 22110296
children; obesity; overweight; BMI; Greek
20.  Very high prevalence of thinness using new international body mass index cut off points among 5-10 year old school children of nandigram, west Bengal, India 
To assess the prevalence of thinness among 5-10 year old school children of Nandigram, Purba Medinipur District of West Bengal, India.
A total of 596 students (323 boys and 288 girls) aged 5-10 years were included in this crosssectional study. Height and weight were measured and the body mass index (BMI) was computed. The new international BMI-based classification cut-off points proposed by Cole et al were utilized to identify thinness.
The overall (age-combined) mean BMI among boys and girls were 13.9 kg/m2 (SD = 1.4) and 13.8 kg/m2 (SD = 1.2), respectively. In general, mean BMI increased with age in both sexes. There was no significant sex difference in mean BMI. The overall (age-combined) prevalence of thinness was 62.9% and 61.6% in boys and girls, respectively.
The present study clearly indicated that the nutritional situation of these children was unsatisfactory.
PMCID: PMC3129089  PMID: 21772872
Body mass index; undernutrition; thinness; IOTF cut off points; nandigram; West Bengal
21.  Moderate agreement between body mass index and measures of waist circumference in the identification of overweight among 5-year-old children; the ‘Be active, eat right’ study 
BMC Pediatrics  2013;13:63.
Body mass index (BMI) is a common indirect method to assess weight status among children. There is evidence that BMI data alone can underestimate overweight-related health risk and that waist circumference (WC) should also be measured. In this study we investigated the agreement between BMI and WC and BMI and the waist-height ratio (WHtR) when used to identify overweight among children.
This cross-sectional population-based study uses baseline data from 5-year-olds (n = 7703) collected by healthcare professionals for the ‘Be active, eat right’ study.
According to age-specific and sex-specific cut-off points for BMI (IOTF, 2000) and WC (Fredriks et al., 2005), the prevalence of overweight (obesity included) was 7.0% and 7.1% among boys, and 11.6% and 10.1% among girls, respectively. For the WHtR the 90th percentile was used as the cut-off point. Among boys, observed proportion of agreement between BMI and WC classification was 0.95, Cohen’s kappa 0.58 (95% CI; 0.53-0.63), and proportions of positive and negative agreement were 0.61 and 0.97, respectively. Observed proportion of agreement between BMI and WHtR classification was 0.92, Cohen’s kappa 0.46 (95% CI; 0.41-0.51), and proportions of positive and negative agreement were 0.51 and 0.95. Children identified as overweight according to WC were relatively tall, and children classified as overweight according to the WHtR only were relatively short (comparable results for girls).
There is moderate agreement between BMI and measures of WC on the presence of overweight among 5-year-olds. If BMI data and cut-offs continue to be used, then part of the group of children identified as overweight according to WC and the WHtR will be omitted. Follow-up of the children classified as overweight according to BMI only, WC only, and WHtR only, will give indications whether WC should be measured in addition to BMI or whether WC should only be measured in certain subgroups (e.g. relatively tall or short children) to identify and monitor overweight in children. This may improve early identification and prevention of overweight and overweight-related health problems in children.
PMCID: PMC3679730  PMID: 23617233
Body mass index; Waist circumference; Overweight; Preschool child; Pediatrics; Prevalence
22.  Polysomnography in Patients With Obstructive Sleep Apnea 
Executive Summary
The objective of this health technology policy assessment was to evaluate the clinical utility and cost-effectiveness of sleep studies in Ontario.
Clinical Need: Target Population and Condition
Sleep disorders are common and obstructive sleep apnea (OSA) is the predominant type. Obstructive sleep apnea is the repetitive complete obstruction (apnea) or partial obstruction (hypopnea) of the collapsible part of the upper airway during sleep. The syndrome is associated with excessive daytime sleepiness or chronic fatigue. Several studies have shown that OSA is associated with hypertension, stroke, and other cardiovascular disorders; many researchers believe that these cardiovascular disorders are consequences of OSA. This has generated increasing interest in recent years in sleep studies.
The Technology Being Reviewed
There is no ‘gold standard’ for the diagnosis of OSA, which makes it difficult to calibrate any test for diagnosis. Traditionally, polysomnography (PSG) in an attended setting (sleep laboratory) has been used as a reference standard for the diagnosis of OSA. Polysomnography measures several sleep variables, one of which is the apnea-hypopnea index (AHI) or respiratory disturbance index (RDI). The AHI is defined as the sum of apneas and hypopneas per hour of sleep; apnea is defined as the absence of airflow for ≥ 10 seconds; and hypopnea is defined as reduction in respiratory effort with ≥ 4% oxygen desaturation. The RDI is defined as the sum of apneas, hypopneas, and abnormal respiratory events per hour of sleep. Often the two terms are used interchangeably. The AHI has been widely used to diagnose OSA, although with different cut-off levels, the basis for which are often unclear or arbitrarily determined. Generally, an AHI of more than five events per hour of sleep is considered abnormal and the patient is considered to have a sleep disorder. An abnormal AHI accompanied by excessive daytime sleepiness is the hallmark for OSA diagnosis. For patients diagnosed with OSA, continuous positive airway pressure (CPAP) therapy is the treatment of choice. Polysomnography may also used for titrating CPAP to individual needs.
In January 2005, the College of Physicians and Surgeons of Ontario published the second edition of Independent Health Facilities: Clinical Practice Parameters and Facility Standards: Sleep Medicine, commonly known as “The Sleep Book.” The Sleep Book states that OSA is the most common primary respiratory sleep disorder and a full overnight sleep study is considered the current standard test for individuals in whom OSA is suspected (based on clinical signs and symptoms), particularly if CPAP or surgical therapy is being considered.
Polysomnography in a sleep laboratory is time-consuming and expensive. With the evolution of technology, portable devices have emerged that measure more or less the same sleep variables in sleep laboratories as in the home. Newer CPAP devices also have auto-titration features and can record sleep variables including AHI. These devices, if equally accurate, may reduce the dependency on sleep laboratories for the diagnosis of OSA and the titration of CPAP, and thus may be more cost-effective.
Difficulties arise, however, when trying to assess and compare the diagnostic efficacy of in-home PSG versus in-lab. The AHI measured from portable devices in-home is the sum of apneas and hypopneas per hour of time in bed, rather than of sleep, and the absolute diagnostic efficacy of in-lab PSG is unknown. To compare in-home PSG with in-lab PSG, several researchers have used correlation coefficients or sensitivity and specificity, while others have used Bland-Altman plots or receiver operating characteristics (ROC) curves. All these approaches, however, have potential pitfalls. Correlation coefficients do not measure agreement; sensitivity and specificity are not helpful when the true disease status is unknown; and Bland-Altman plots measure agreement (but are helpful when the range of clinical equivalence is known). Lastly, receiver operating characteristics curves are generated using logistic regression with the true disease status as the dependent variable and test values as the independent variable. Thus, each value of the test is used as a cut-point to measure sensitivity and specificity, which are then plotted on an x-y plane. The cut-point that maximizes both sensitivity and specificity is chosen as the cut-off level to discriminate between disease and no-disease states. In the absence of a gold standard to determine the true disease status, ROC curves are of minimal value.
At the request of the Ontario Health Technology Advisory Committee (OHTAC), MAS has thus reviewed the literature on PSG published over the last two years to examine new developments.
Review Strategy
There is a large body of literature on sleep studies and several reviews have been conducted. Two large cohort studies, the Sleep Heart Health Study and the Wisconsin Sleep Cohort Study, are the main sources of evidence on sleep literature.
To examine new developments on PSG published in the past two years, MEDLINE, EMBASE, MEDLINE In-Process & Other Non-Indexed Citations, the Cochrane Database of Systematic Reviews and Cochrane CENTRAL, INAHTA, and websites of other health technology assessment agencies were searched. Any study that reported results of in-home or in-lab PSG was included. All articles that reported findings from the Sleep Heart Health Study and the Wisconsin Sleep Cohort Study were also reviewed.
Diffusion of Sleep Laboratories
To estimate the diffusion of sleep laboratories, a list of sleep laboratories licensed under the Independent Health Facility Act was obtained. The annual number of sleep studies per 100,000 individuals in Ontario from 2000 to 2004 was also estimated using administrative databases.
Summary of Findings
Literature Review
A total of 315 articles were identified that were published in the past two years; 227 were excluded after reviewing titles and abstracts. A total of 59 articles were identified that reported findings of the Sleep Heart Health Study and the Wisconsin Sleep Cohort Study.
Based on cross-sectional data from the Wisconsin Sleep Cohort Study of 602 men and women aged 30 to 60 years, it is estimated that the prevalence of sleep-disordered breathing is 9% in women and 24% in men, on the basis of more than five AHI events per hour of sleep. Among the women with sleep disorder breathing, 22.6% had daytime sleepiness and among the men, 15.5% had daytime sleepiness. Based on this, the prevalence of OSA in the middle-aged adult population is estimated to be 2% in women and 4% in men.
Snoring is present in 94% of OSA patients, but not all snorers have OSA. Women report daytime sleepiness less often compared with their male counterparts (of similar age, body mass index [BMI], and AHI). Prevalence of OSA tends to be higher in older age groups compared with younger age groups.
Diagnostic Value of Polysomnography
It is believed that PSG in the sleep laboratory is more accurate than in-home PSG. In the absence of a gold standard, however, claims of accuracy cannot be substantiated. In general, there is poor correlation between PSG variables and clinical variables. A variety of cut-off points of AHI (> 5, > 10, and > 15) are arbitrarily used to diagnose and categorize severity of OSA, though the clinical importance of these cut-off points has not been determined.
Recently, a study of the use of a therapeutic trial of CPAP to diagnose OSA was reported. The authors studied habitual snorers with daytime sleepiness in the absence of other medical or psychiatric disorders. Using PSG as the reference standard, the authors calculated the sensitivity of this test to be 80% and its specificity to be 97%. Further, they concluded that PSG could be avoided in 46% of this population.
Obstructive Sleep Apnea and Obesity
Obstructive sleep apnea is strongly associated with obesity. Obese individuals (BMI >30 kg/m2) are at higher risk for OSA compared with non-obese individuals and up to 75% of OSA patients are obese. It is hypothesized that obese individuals have large deposits of fat in the neck that cause the upper airway to collapse in the supine position during sleep. The observations reported from several studies support the hypothesis that AHIs (or RDIs) are significantly reduced with weight loss in obese individuals.
Obstructive Sleep Apnea and Cardiovascular Diseases
Associations have been shown between OSA and comorbidities such as diabetes mellitus and hypertension, which are known risk factors for myocardial infarction and stroke. Patients with more severe forms of OSA (based on AHI) report poorer quality of life and increased health care utilization compared with patients with milder forms of OSA. From animal models, it is hypothesized that sleep fragmentation results in glucose intolerance and hypertension. There is, however, no evidence from prospective studies in humans to establish a causal link between OSA and hypertension or diabetes mellitus. It is also not clear that the associations between OSA and other diseases are independent of obesity; in most of these studies, patients with higher values of AHI had higher values of BMI compared with patients with lower AHI values.
A recent meta-analysis of bariatric surgery has shown that weight loss in obese individuals (mean BMI = 46.8 kg/m2; range = 32.30–68.80) significantly improved their health profile. Diabetes was resolved in 76.8% of patients, hypertension was resolved in 61.7% of patients, hyperlipidemia improved in 70% of patients, and OSA resolved in 85.7% of patients. This suggests that obesity leads to OSA, diabetes, and hypertension, rather than OSA independently causing diabetes and hypertension.
Health Technology Assessments, Guidelines, and Recommendations
In April 2005, the Centers for Medicare and Medicaid Services (CMS) in the United States published its decision and review regarding in-home and in-lab sleep studies for the diagnosis and treatment of OSA with CPAP. In order to cover CPAP, CMS requires that a diagnosis of OSA be established using PSG in a sleep laboratory. After reviewing the literature, CMS concluded that the evidence was not adequate to determine that unattended portable sleep study was reasonable and necessary in the diagnosis of OSA.
In May 2005, the Canadian Coordinating Office of Health Technology Assessment (CCOHTA) published a review of guidelines for referral of patients to sleep laboratories. The review included 37 guidelines and associated reviews that covered 18 applications of sleep laboratory studies. The CCOHTA reported that the level of evidence for many applications was of limited quality, that some cited studies were not relevant to the recommendations made, that many recommendations reflect consensus positions only, and that there was a need for more good quality studies of many sleep laboratory applications.
As of the time of writing, there are 97 licensed sleep laboratories in Ontario. In 2000, the number of sleep studies performed in Ontario was 376/100,000 people. There was a steady rise in sleep studies in the following years such that in 2004, 769 sleep studies per 100,000 people were performed, for a total of 96,134 sleep studies. Based on prevalence estimates of the Wisconsin Sleep Cohort Study, it was estimated that 927,105 people aged 30 to 60 years have sleep-disordered breathing. Thus, there may be a 10-fold rise in the rate of sleep tests in the next few years.
Economic Analysis
In 2004, approximately 96,000 sleep studies were conducted in Ontario at a total cost of ~$47 million (Cdn). Since obesity is associated with sleep disordered breathing, MAS compared the costs of sleep studies to the cost of bariatric surgery. The cost of bariatric surgery is $17,350 per patient. In 2004, Ontario spent $4.7 million per year for 270 patients to undergo bariatric surgery in the province, and $8.2 million for 225 patients to seek out-of-country treatment. Using a Markov model, it was concluded that shifting costs from sleep studies to bariatric surgery would benefit more patients with OSA and may also prevent health consequences related to diabetes, hypertension, and hyperlipidemia. It is estimated that the annual cost of treating comorbid conditions in morbidly obese patients often exceeds $10,000 per patient. Thus, the downstream cost savings could be substantial.
Considerations for Policy Development
Weight loss is associated with a decrease in OSA severity. Treating and preventing obesity would also substantially reduce the economic burden associated with diabetes, hypertension, hyperlipidemia, and OSA. Promotion of healthy weights may be achieved by a multisectorial approach as recommended by the Chief Medical Officer of Health for Ontario. Bariatric surgery has the potential to help morbidly obese individuals (BMI > 35 kg/m2 with an accompanying comorbid condition, or BMI > 40 kg/m2) lose weight. In January 2005, MAS completed an assessment of bariatric surgery, based on which OHTAC recommended an improvement in access to these surgeries for morbidly obese patients in Ontario.
Habitual snorers with excessive daytime sleepiness have a high pretest probability of having OSA. These patients could be offered a therapeutic trial of CPAP to diagnose OSA, rather than a PSG. A majority of these patients are also obese and may benefit from weight loss. Individualized weight loss programs should, therefore, be offered and patients who are morbidly obese should be offered bariatric surgery.
That said, and in view of the still evolving understanding of the causes, consequences and optimal treatment of OSA, further research is warranted to identify which patients should be screened for OSA.
PMCID: PMC3379160  PMID: 23074483
23.  A Study of Insulin Resistance by HOMA-IR and its Cut-off Value to Identify Metabolic Syndrome in Urban Indian Adolescents 
Objective: Insulin resistance (IR) and associated metabolic abnormalities are increasingly being reported in the adolescent population. Cut-off value of homeostasis model of assessment IR (HOMA-IR) as an indicator of metabolic syndrome (MS) in adolescents has not been established. This study aimed to investigate IR by HOMA-IR in urban Indian adolescents and to establish cut-off values of HOMA-IR for defining MS.
Methods: A total of 691 apparently healthy adolescents (295 with normal body mass index (BMI), 205 overweight, and 199 obese) were included in this cross-sectional study. MS in adolescents was defined by International Diabetes Federation (IDF) and Adult Treatment Panel III (ATP III) criteria. IR was calculated using the HOMA model.
Results: Mean height, waist circumference (WC), waist/hip ratio (WHR), waist/height ratio (WHtR), and blood pressure were significantly higher in boys as compared to girls. The HOMA-IR values increased progressively from normal weight to obese adolescents in both sexes. Mean HOMA-IR values increased progressively according to sexual maturity rating in both sexes. HOMA-IR value of 2.5 had a sensitivity of >70% and specificity of >60% for MS. This cut-off identified larger number of adolescents with MS in different BMI categories (19.7% in normal weight, 51.7% in overweight, and 77.0% in obese subjects) as compared to the use of IDF or ATP III criteria for diagnosing MS. Odds ratio for having IR (HOMA-IR of >2.5) was highest with WHtR (4.9, p <0.0001) and WC (4.8, p <0.0001), compared to WHR (3.3, p <0.0001).
Conclusions: In Indian adolescents, HOMA-IR increased with sexual maturity and with progression from normal to obese. A HOMA-IR cut-off of 2.5 provided the maximum sensitivity and specificity in diagnosing MS in both genders as per ATP III and IDF criteria.
Conflict of interest:None declared.
PMCID: PMC3890224  PMID: 24379034
insulin resistance; metabolic syndrome; HOMA-IR; adolescents
24.  Validation of obesity based on self-reported data in Spanish women participants in breast cancer screening programmes 
BMC Public Health  2011;11:960.
Measurement of obesity using self-reported anthropometric data usually involves underestimation of weight and/or overestimation of height. The dual aim of this study was, first, to ascertain and assess the validity of new cut-off points, for both overweight and obesity, using self-reported Body Mass Index furnished by women participants in breast cancer screening programmes, and second, to estimate and validate a predictive model that allows recalculate individual BMI based on self-reported data.
The study covered 2927 women enrolled at 7 breast cancer screening centres. At each centre, women were randomly selected in 2 samples, in a ratio of 2:1. The larger sample (n = 1951) was used to compare the values of measured and self-reported weight and height, to ascertain new overweight and obesity cut-off points with self-reported data, using ROC curves, and to estimate a predictive model of real BMI using a regression model. The second sample (n = 976) was used to validate the proposed cut-off points and the predictive model.
Whereas reported prevalence of obesity was 19.8%, measured prevalence was 28.2%. The sensitivity and specificity of this classification would be maximised if the new cut-off points were 24.30 kg/m2 for overweight and 28.39 kg/m2 for obesity. The probability of classifying women correctly in their real weight categories on the basis of these points was 82.5% in the validation sample. Sensitivity and specificity for determining obesity using the new cut-off point in the validation sample were 90.0% and 92.3% respectively. The predictive model for real BMI included the self-reported BMI, age and educational level (university studies vs lower levels of education). This model succeeded in correctly classifying 90.5% of women according to BMI categories, but its performance was similar to that obtained with the new cut-off points.
Quantification of self-reported obesity entails a considerable underestimation of this problem, thereby questioning its validity. The new cut-off points established in this study and the predictive equation both allow for more accurate estimation of these prevalences.
PMCID: PMC3268784  PMID: 22208614
25.  Sedentary behaviors, physical activity behaviors, and body fat in 6-year-old children: the Generation R Study 
Childhood overweight and obesity is a major public health concern. Knowledge on modifiable risk factors is needed to design effective intervention programs. This study aimed to assess associations of children’s sedentary behaviors (television viewing and computer game use) and physical activity behaviors (sports participation, outdoor play, and active transport to/from school) with three indicators of body fat, i.e., percent fat mass, body mass index (BMI) standard deviation scores, and weight status (normal weight, overweight).
Cross-sectional data from 5913 6-year-old ethnically diverse children were analyzed. Children’s weight and height were objectively measured and converted to BMI. Weight status was defined according to age- and sex-specific cut-off points of the International Obesity Task Force. BMI standard deviation scores were created, based on Dutch reference growth curves. Fat mass was measured my dual-energy X-ray absorptiometry (DXA). Sedentary and physical activity behaviors were assessed by parent-reported questionnaires. Series of logistic and linear regression analyses were performed, controlling for confounders (i.e., socio-demographic factors, family lifestyle factors, and other sedentary behaviors and physical activity behaviors).
Sports participation was inversely associated with fat mass (p < 0.001), even after adjustment for socio-demographic factors, family lifestyle factors, and other sedentary behaviors and physical activity behaviors. No other independent associations were observed.
The results of this study indicate that sports participation is inversely associated with percent body fat among ethnically diverse 6-year-old children. More research in varied populations including objective measurements and longitudinal designs are needed to confirm these current results.
PMCID: PMC4145220  PMID: 25124336
Body fat; Overweight; Lifestyle; Physical activity; Sedentary; Children

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