Six new loci associated with body mass index highlight a neuronal influence on body weight regulation

Common variants at only two loci, FTO and MC4R, have been reproducibly associated with body mass index (BMI) in humans. To identify additional loci, we conducted meta-analysis of 15 genome-wide association studies for BMI (n > 32,000) and followed up top signals in 14 additional cohorts (n > 59,000). We strongly confirm FTO and MC4R and identify six additional loci (P < 5 x 10(-8)): TMEM18, KCTD15, GNPDA2, SH2B1, MTCH2 and NEGR1 (where a 45-kb deletion polymorphism is a candidate causal variant). Several of the likely causal genes are highly expressed or known to act in the central nervous system (CNS), emphasizing, as in rare monogenic forms of obesity, the role of the CNS in predisposition to obesity.

Trends in adult body-mass index in 200 countries from 1975 to 2014: a pooled analysis of 1698 population-based measurement studies with 19·2 million participants

Background Underweight and severe and morbid obesity are associated with highly elevated risks of adverse health outcomes. We estimated trends in mean body-mass index (BMI), which characterises its population distribution, and in the prevalences of a complete set of BMI categories for adults in all countries. Methods We analysed, with use of a consistent protocol, population-based studies that had measured height and weight in adults aged 18 years and older. We applied a Bayesian hierarchical model to these data to estimate trends from 1975 to 2014 in mean BMI and in the prevalences of BMI categories (<18·5 kg/m2 [underweight], 18·5 kg/m2 to <20 kg/m2, 20 kg/m2 to <25 kg/m2, 25 kg/m2 to <30 kg/m2, 30 kg/m2 to <35 kg/m2, 35 kg/m2 to <40 kg/m2, ≥40 kg/m2 [morbid obesity]), by sex in 200 countries and territories, organised in 21 regions. We calculated the posterior probability of meeting the target of halting by 2025 the rise in obesity at its 2010 levels, if post-2000 trends continue. Findings We used 1698 population-based data sources, with more than 19·2 million adult participants (9·9 million men and 9·3 million women) in 186 of 200 countries for which estimates were made. Global age-standardised mean BMI increased from 21·7 kg/m2 (95% credible interval 21·3–22·1) in 1975 to 24·2 kg/m2 (24·0–24·4) in 2014 in men, and from 22·1 kg/m2 (21·7–22·5) in 1975 to 24·4 kg/m2 (24·2–24·6) in 2014 in women. Regional mean BMIs in 2014 for men ranged from 21·4 kg/m2 in central Africa and south Asia to 29·2 kg/m2 (28·6–29·8) in Polynesia and Micronesia; for women the range was from 21·8 kg/m2 (21·4–22·3) in south Asia to 32·2 kg/m2 (31·5–32·8) in Polynesia and Micronesia. Over these four decades, age-standardised global prevalence of underweight decreased from 13·8% (10·5–17·4) to 8·8% (7·4–10·3) in men and from 14·6% (11·6–17·9) to 9·7% (8·3–11·1) in women. South Asia had the highest prevalence of underweight in 2014, 23·4% (17·8–29·2) in men and 24·0% (18·9–29·3) in women. Age-standardised prevalence of obesity increased from 3·2% (2·4–4·1) in 1975 to 10·8% (9·7–12·0) in 2014 in men, and from 6·4% (5·1–7·8) to 14·9% (13·6–16·1) in women. 2·3% (2·0–2·7) of the world's men and 5·0% (4·4–5·6) of women were severely obese (ie, have BMI ≥35 kg/m2). Globally, prevalence of morbid obesity was 0·64% (0·46–0·86) in men and 1·6% (1·3–1·9) in women. Interpretation If post-2000 trends continue, the probability of meeting the global obesity target is virtually zero. Rather, if these trends continue, by 2025, global obesity prevalence will reach 18% in men and surpass 21% in women; severe obesity will surpass 6% in men and 9% in women. Nonetheless, underweight remains prevalent in the world's poorest regions, especially in south Asia.

Body mass index values for newborns according to gestational age

Objective: The combination of twho anthropometric parameters has been more appropriate to assess body composition and proportions in children, with special attention to the Body Mass Index (BMI), as it relates weight and length. However the BMI values for the neonatal period have not been determined yet. This study shows the BMI for newborns at different gestational ages represented in a normal smoothed percentile curve. Methods: Retrospective study including 2,406 appropriate for gestational age newborns following the Alexander et al curve (1996) from 29 to 42 weeks of gestational age. Weight and lenght were measured following standard procedures. For the construction aof a normal smoothed percentile curve, the 3(rd) 5(th), 10(th), 25(th), 5(th), 75(th), 90(th) and 95(th) percentiles were determined and a statistical procedure based on the mathematical model ""sinosuoidal fit"" was applied to establish a curve that estimates biological growth parameters. Results: The Body Mass Index values for gestational age in all percentiles shows a steady increase up to 38 weeks, levels off up to the 40(th) week, followed by a slight decrease to the 42(nd) week in both genders. Conclusion: The results show a direct correlation between gestational age and Body Mass Index for both genders in the nine percentiles, and can provide a useful reference to assess intra-uterine proportional growth.

Genetic studies of body mass index yield new insights for obesity biology

Obesity is heritable and predisposes to many diseases. To understand the genetic basis of obesity better, here we conduct a genome-wide association study and Metabochip meta-analysis of body mass index (BMI), a measure commonly used to define obesity and assess adiposity, in upto 339,224 individuals. This analysis identifies 97 BMI-associated loci (P < 5 x 10(-8)), 56 of which are novel. Five loci demonstrate clear evidence of several independent association signals, and many loci have significant effects on other metabolic phenotypes. The 97 loci account for similar to 2.7% of BMI variation, and genome-wide estimates suggest that common variation accounts for >20% of BMI variation. Pathway analyses provide strong support for a role of the central nervous systemin obesity susceptibility and implicate new genes and pathways, including those related to synaptic function, glutamate signalling, insulin secretion/action, energy metabolism, lipid biology and adipogenesis.

Relationship between body mass index and the use of healthcare services in Australia

Objective: To examine the relationship between body mass index (BMI) and the use of medical and preventive health services. Research Methods and Procedures: This study involved secondary analysis of weighted data from the Australian 1995 National Health Survey. The study was a population survey designed to obtain national benchmark information about a range of health-related issues. Data were available from 17,033 men and 17,174 women, 20 years or age. BMI, based on self-reported weight and height, was analyzed in relation to the use of medical services and preventive health services. Results: A positive relationship was found between BMI and medical service use, such as medication use, visits to hospital accident and emergency departments (for women only); doctor visits, visits to a hospital outpatient clinics; and visits to other health professionals (for women only). A negative relationship was found in women between BMI and preventive health services. Underweight women were found to be significantly less likely to have Papanicolaou smear tests, breast examinations, and mammograms. Discussion: This research shows that people who fall outside the healthy weight range are more likely to use a range of medical services. Given that the BMI of industrialized populations appears to be increasing, this has important ramifications for health service planning and reinforces the need for obesity prevention strategies at a population level.

Foods prepared outside the home: association with selected nutrients and body mass index in adult Australians

Objective: To determine the proportion of energy from foods prepared outside the home (FPOH) and the relationships with energy and nutrient intakes and body mass index (BMI).

Design: A nutrition survey of a representative sample of the Australian population aged 18 years and over (n = 10 863). Measure used was a 24-hour dietary recall. Underreporters (energy intake/estimated basal metabolic rate (EI/BMR) <0.9) were excluded from analysis. Daily energy and selected nutrient intakes were calculated using a 1996 nutrient composition database for all foods/beverages during the 24-hour period.

Results: On average FPOH contributed a significant 13% to total energy intake. About a third of the sample had consumed FPOH in the last 24 hours and on average this group consumed a third of their total energy as FPOH. The relative contributions of fat (for men and women) and alcohol (for women) were significantly higher for those in the top tertile of FPOH consumers. The intakes of fibre and selected micronutrients (calcium, iron, zinc, folate and vitamin C) were significantly lower in this group. After adjustment for age and income no relationship between FPOH and BMI was observed.

Conclusions: FPOH make a significant contribution to the energy intake of a third of the Australian population. FPOH contribute to poor nutritional intakes. Altering the supply of FPOH may be an effective means of improving diets at a population level.

Body mass index and parent-reported self-estem in elementary school children: evidence for a causal relationship.

OBJECTIVE: To clarify relationships between body mass index (BMI) and self-esteem in young children at a population level. To assess whether low self-esteem precedes or follows development of overweight/obesity in children. DESIGN: Prospective cohort study in elementary schools throughout Victoria, Australia. Child BMI and self-esteem were measured in 1997 and 2000. SUBJECTS: Random sample of 1,157 children who were in the first 4 y of elementary school (aged 5-10 y) at baseline. MEASURES: BMI was calculated from measured height and weight, then transformed to z-scores. Children were classified as nonoverweight, overweight or obese based on international cut-points. Low child self-esteem was defined as a score below the 15th percentile on the self-esteem subscale of the parent-reported Child Health Questionnaire. RESULTS: Overweight/obese children had lower median self-esteem scores than nonoverweight children at both timepoints, especially at follow-up. After accounting for baseline self-esteem, higher baseline BMI z-score predicted poorer self-esteem at follow-up (P=0.008). After accounting for baseline BMI z-score, poorer baseline self-esteem did not predict higher BMI z-score at follow-up. While nonoverweight children with low baseline self-esteem were more likely to develop overweight/obesity (OR=2.1, 95% CI=1.2, 3.6), this accounted for only a small proportion of the incidence of overweight. CONCLUSIONS: Our data show an increasingly strong association between lower self-esteem and higher body mass across the elementary school years. Overweight/obesity precedes low self-esteem in many children, suggesting a causal relationship. This indicates that prevention and management strategies for childhood overweight/obesity need to begin early to minimise the impact on self-esteem.

Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies

A WHO expert consultation addressed the debate about interpretation of recommended body-mass index (BMI) cut-off points for determining overweight and obesity in Asian populations, and considered whether population-specific cut-off points for BMI are necessary. They reviewed scientific evidence that suggests that Asian populations have different associations between BMI, percentage of body fat, and health risks than do European populations. The consultation concluded that the proportion of Asian people with a high risk of type 2 diabetes and cardiovascular disease is substantial at BMIs lower than the existing WHO cut-off point for overweight (25 kg/m2). However, available data do not necessarily indicate a clear BMI cut-off point for all Asians for overweight or obesity. The cut-off point for observed risk varies from 22kg/m2 to 25kg/m2 in different Asian populations; for high risk it varies from 26kg/m2 to 31kg/m2. No attempt was made, therefore, to redefine cut-off points for each population separately. The consultation also agreed that the WHO BMI cut-off points should be retained as international classifications. The consultation identified further potential public health action points (23·0, 27·5, 32·5, and 37·5 kg/m2) along the continuum of BMI, and proposed methods by which countries could make decisions about the definitions of increased risk for their population.

Dietary patterns throughout adult life are associated with body mass index, waist circumference, blood pressure, and red cell folate

Dietary patterns are important in the prevention of chronic disease; however, there are few studies that include repeat measures of dietary patterns. The objective of this study was to assess the relations between dietary patterns during adult life (at ages 36, 43, and 53 y) and risk factors for chronic disease at age 53 y. Participants of a longitudinal study of health completed a 5-d food diary at 3 occasions during adult life (n = 1265). Factor analysis was used to identify dietary patterns and a pattern score was calculated from the consumption of the food items in each dietary pattern. Means and 95% CI for dietary pattern scores were calculated for each risk factor category using random effects models adjusted for socio-demographic and health-related behaviors. In women, the fruit, vegetables, and dairy pattern was inversely associated with BMI (P < 0.004), waist circumference (P = 0.0007), blood pressure (P = 0.02), and was positively associated with red cell folate (P < 0.03). The ethnic foods and alcohol pattern was also inversely associated with blood pressure (P = 0.008), whereas the meat, potatoes and sweet foods pattern was positively associated with glycated hemoglobin (P = 0.01). In men, a mixed pattern was inversely associated with waist circumference (P = 0.02) and blood pressure (P = 0.01), whereas there were no significant associations with the ethnic foods and alcohol pattern. Specific dietary patterns throughout adult life were associated with chronic disease risk factors.

Stability of television viewing and electronic game/computer use in a prospective cohort study of Australian children: relationship with body mass index

Background
While much cross-sectional data is available, there have been few longitudinal investigations of patterns of electronic media use in children. Further, the possibility of a bi-directional relationship between electronic media use and body mass index in children has not been considered. This study aimed to describe longitudinal patterns of television viewing and electronic game/computer use, and investigate relationships with body mass index (BMI).
Methods
This prospective cohort study was conducted in elementary schools in Victoria, Australia. 1278 children aged 5–10 years at baseline and 8–13 years at follow-up had their BMI calculated, from measured height and weight, and transformed to z-scores based on US 2000 growth data. Weight status (non-overweight, overweight and obese) was based on international BMI cut-off points. Weekly television viewing and electronic game/computer use were reported by parents, these were summed to generate total weekly screen time. Children were classified as meeting electronic media use guidelines if their total screen time was ≤14 hrs/wk.
Results
Electronic media use increased over the course of the study; 40% met guidelines at baseline but only 18% three years later. Television viewing and electronic game/computer use tracked moderately and total screen time was positively associated with adiposity cross-sectionally. While weaker relationships with adiposity were observed longitudinally, baseline z-BMI and weight status were positively associated with follow-up screen time and baseline screen time was positively associated with z-BMI and weight status at follow-up. Children who did not meet guidelines at baseline had significantly higher z-BMI and were more likely to be classified as overweight/obese at follow-up.

Conclusion
Electronic media use in Australian elementary school children is high, increases with age and tracks over time. There appears to be a bi-directional association suggesting that interventions targeting reductions in either screen time or adiposity may have a positive effect on both screen time and adiposity.

Stability of body mass index in Australian children: a prospective cohort study across the middle childhood years

Objective: To investigate the prevalence and incidence of overweight and obesity, the frequency of overweight resolution and the influence of parental adiposity during middle childhood.

Design: As part of a prospective cohort study, height and weight were measured in 1997 and 2000/2001. Children were classified as non-overweight, overweight or obese based on standard international definitions. Body mass index (BMI) was transformed into age- and gender-specific Z-scores employing the LMS method and 2000 growth chart data of the Centers for Disease Control and Prevention. Parents self-reported height and weight, and were classified as underweight, healthy weight, overweight or obese based on World Health Organization definitions.

Setting: Primary schools in Victoria, Australia.

Subjects: In total, 1438 children aged 5–10 years at baseline.

Results: The prevalence of overweight and obesity increased between baseline (15.0 and 4.3%, respectively) and follow-up (19.7 and 4.8%, respectively; P < 0.001 for increase in overweight and obesity combined). There were 140 incident cases of overweight (9.7% of the cohort) and 24 of obesity (1.7% of the cohort); only 3.8% of the cohort (19.8% of overweight/obese children) resolved to a healthy weight. The stability of child adiposity as measured by BMI category (84.8% remained in the same category) and BMI Z-score (r = 0.84; mean change = −0.05) was extremely high. Mean change in BMI Z-score decreased with age (linear trend β = 0.03, 95% confidence interval 0.01–0.05). The influence of parental adiposity largely disappeared when children's baseline BMI was adjusted for.

Conclusions: During middle childhood, the incidence of overweight/obesity exceeds the proportion of children resolving to non-overweight. However, for most children adiposity remains stable, and stability appears to increase with age. Prevention strategies targeting children in early childhood are required.

Change in women's body mass index and waist circumference, 1997 to 2002: the Nepean study

Objective: To investigate character istics associated with body mass index (BMI) and waist circumference stability over a five-year period in women with school-age children.

Methods: Women with 7–8 year-old children from western Sydney, Australia, had anthropometric measures taken in 1996/97 (n====436) and five years later (n=327). Socio-demographic characteristics examined at baseline included age, socioeconomic status, smoking, and number of children.

Results: Over five years, less than half of the women maintained a stable BMI (38.8%) or waist circumference (31.5%), with the majority gaining in both indicators of adiposity. BMI and socio-demographic characteristics were not predictive of BMI or waist circumference stability or decrease.

Conclusions and Implications: Total and abdominal adiposity increased in these Australian women who have children. The results support the need to develop effective weight gain prevention initiatives.

Family average income and body mass index above the healthy weight range among urban and rural resicents in regional Mainland China

Objective: To explore the relationship between family average income (FAI; an index of socio-economic status) and body mass index (BMI; a widely used, inexpensive indicator of weight status) above the healthy weight range in a region of Mainland China. Design: Population-based cross-sectional study, conducted between October 1999 and March 2000 on a sample of regular local residents aged 35 years or older who were selected by random cluster sampling. Setting: Forty-five administrative villages selected from three urban districts and two rural counties of Nanjing municipality, Mainland China, with a regional population of 5.6 million. Subjects: In total, 29 340 subjects participated; 67.7% from urban and 32.3% from rural areas; 49.8% male and 50.2% female. The response rate among eligible participants was 90.1%. Results: The proportion of participants classified as overweight was 30.5%, while 7.8% were identified as obese. After adjusting for possible confounding variables (age, gender, area of residence, educational level, occupational and leisure-time physical activity, daily vegetable consumption and frequency of red meat intake), urban participants were more likely to be overweight or obese relative to their rural counterparts, more women than men were obese, and participants in the lowest FAI tertile were the least likely to be above the healthy weight range. Conclusions: The proportion of adults with BMI above the healthy weight range was positively related to having a higher socio-economic status (indexed by FAI) in a regional Chinese population.

Television, computer use and body mass index in Australian primary school children

Objective: To investigate relationships between children's body mass index (BMI) and parent reports of children's television and video game/computer habits, controlling for other potential risk factors for paediatric obesity.

Methods: Child BMI was calculated from measured height and weight collected in 1997 as part of a large, representative, cross-sectional study of children in Victoria, Australia. Parents reported the amount of time children watched television and used video games/computers, children's eating and activity habits, parental BMI and sociodemographic details.

Results: A total of 2862 children aged 5−13 years participated. Child mean BMI z-score was significantly related to television (F = 10.2₃, P < 0.001) but not video game/computer time (F = 2.2₃, P = 0.09), but accounted for only 1 and 0.2% of total BMI variance, respectively. When parental BMI, parental education, number of siblings, food intake, organized exercise and general activity level were included, television ceased to be independently significantly related to child BMI. Using adjusted logistic regression, the odds of being overweight and obese generally increased with increasing television viewing. No relationship was found for video game/computer use.
Conclusions: A small proportion of variance in child BMI was related to television, but not video game/computer time. This was far outweighed by the influence of other variables. Causal pathways are likely to be complex and interrelated.