Second, WHR is not useful in practical risk management as the ratio could remain constant when the weight of individual increases or decreases. A health risk classification based on WC is suggested to be more useful for health assessment than either BMI or WHR, alone or in combination [ 19 , 21 — 23 ]. The relation between WC and clinical outcome is consistently strong for diabetes risk, coronary heart diseases, and all-cause and selected cause-specific mortality rates, and WC is a stronger predictor of cardiometabolic risks than is BMI [ 13 ].
However, the influence of the optimal cutoff values of WC by sex, age and race-ethnicity as suggested by previous studies raises the problem of applying WC for obesity assessment Table 3 [ 14 , 25 , 26 ]. Sex-specific WC and risk of metabolic complications associated with obesity in Caucasians. Source: WHO [ 11 ]. Source: James [ 25 ]. WHtR has been proposed as another rapid and simple screening tool for assessing obesity [ 27 ].
WHtR values above 0. The results were also supported by prospective studies [ 15 , 27 ]. An advantage of using WHtR over WC for assessing obesity is that the same cutoffs can be set for men and women, for children and adults, and for different ethnic groups [ 27 ]. There are ethnic variations in the association between adiposity and health, and Asian populations are generally more susceptible to the development of obesity-related illnesses and morbidity than Caucasian populations at any given level of BMI or WC [ 3 , 29 — 31 ].
These variations in the association between BMI or WC and risk of obesity-related illnesses and morbidity, and between BMI and body fatness have raised the need for population-specific BMI and waist classification cutoff points for defining obesity. However, the cutoff point for observed risk varies from Defining overweight and obesity in children and adolescents is complicated as height is still increasing and body composition changes over time.
Different measures and references such as weight-for-height, BMI percentiles, and skinfold thickness have been used [ 11 , 34 ]. Recently, BMI has been increasingly accepted as a valid indirect measure of adiposity in children and adolescents [ 35 , 36 ].
Cole et al. However, the reference data sets do not adequately represent non-Western populations, and little is known about whether or not BMIs above these cutoff points are related to health consequences for children across populations. Therefore, from onwards, the WHO released two new sets of growth standards for infants and young children [ 37 ], and school aged children and adolescents [ 38 ], respectively.
The standards for infants and young children was developed based on healthy, breast-fed children from around the world [ 39 , 40 ]. A recent international survey also proposed a lower cutoff BMI value of 17 as definition of thinness in children and adolescents [ 42 ]. With aging, body composition changes and height decreases, affecting the interpretation of anthropometric data.
Older persons generally have more fat than younger adults do at any given BMI, and absolute levels of WC indicate more visceral fat in older persons than in younger persons, because relatively more fat accumulates in the abdomen and less fat at the extremities as people age [ 43 ]. In general, BMI is a common method to diagnose obesity in older adults, but because of height and body composition changes with ageing, the cutoff values applied to adults might have to be reconsidered in old subjects [ 44 , 45 ].
In contrary to the young or middle-aged population, numerous studies have reported a J- or U-shaped relationship between BMI and mortality in older adults, and underweight is hazardous whereas mild-grade overweight, obesity and even central obesity might be protective for older adults [ 46 — 48 ]. Due to the progressive age-decline in stature, using BMI to classify obesity may overestimate adiposity in the elderly [ 49 ]. Furthermore, BMI cannot make a discrepancy between fat and muscle mass [ 45 ].
The reliability of BMI as an index of obesity is thus questionable, and therefore, other anthropometric indices are proposed to determine the degree of fatness in the elderly. However, the choice of measurement and the cutoff values in predicting mortality or other cardiovascular risks in the elderly population is still uncertain [ 50 — 53 ].
In summary, since the associations between adult values for overweight and obesity and certain adverse health outcomes in elderly populations show conflicting results with a suggestion that higher values may not result in adverse health outcomes, it may not be appropriate to apply existing adult values to elderly people aged 70 year and over.
In view of the rapidly growing numbers of people in this age group in many developed countries with population ageing, this has important health implications in terms of health promotion and treatment targets.
Further research is indicated in establishing criteria for a healthy weight in people aged 70 years and over, using relevant health outcomes such as functional independence in addition to disease occurrence. The emphasis may likely be on weight maintenance rather than reduction at the extreme of old age, when ability to modify lifestyle may be limited and quality of life may assume greater importance. Numerous epidemiological studies have been conducted to show the relationship between excess weight, abdominal fatness and risk of a wide range of illnesses [ 6 , 54 — 56 ].
Table 4 summarizes the approximate relative risk of physical health problems associated with obesity [ 57 ]. Of all physical health problems, type II diabetes has the strongest association with obesity. A meta-analysis examined the relative risk of incidence of various co-morbidities related to obesity and overweight from 89 studies [ 6 ]. Obesity, as defined by BMI, showed the strongest association with incidences of type II diabetes as compared to other co-morbidities. Obesity predisposes an individual to a number of cardiovascular risks including hypertension, dyslipidemia and coronary heart disease [ 6 , 59 ].
In the Multi-Ethnic Study of Atherosclerosis, which assessed the association between obesity and cardiovascular risk factors and subclinical vascular disease in 6, persons aged 45 to 84 years, showed that a higher BMI was associated with more adverse levels of blood pressure, lipoproteins, and fasting glucose, and higher prevalence ratios of hypertension [ 60 ]. A number of reviews have considered the association of obesity and cancer [ 6 , 62 — 64 ]. Data from a meta-analysis showed that the pooled relative risks across categories of BMI for various cancers ranged from 1. The recent report by the World Cancer Research Fund and the American Institute for Cancer Research [ 57 ] also suggested that there was convincing evidence that overweight and obesity increased the risk of cancers of the esophagus, pancreas, colon and rectum, breast postmenopausal , endometrium, and kidney.
In addition, there was convincing evidence to support that abdominal fatness was a cause of colon cancer and may probably increase the risk of cancers of breast postmenopausal and endometrium. There is a wealth of evidence to show that excess weight is an important risk factor in the development of other illnesses, including respiratory diseases [ 54 ], chronic kidney diseases [ 56 ], musculoskeletal disorders [ 65 , 66 ], gastrointestinal and hepatic disorders [ 67 , 68 ], lower physical functioning performance [ 69 ] and psychological problems [ 11 ]. The etiology of obesity is multifactorial, involving complex interactions among the genetic background, hormones and different social and environmental factors, such as sedentary lifestyle and unhealthy dietary habits [ 11 ].
Table 5 lists the key factors that might promote or protect against weight gain and obesity as suggested by the WHO [ 70 ]. Summary of strength of evidence on factors that might promote or protect against weight gain and obesity. Source: WHO [ 70 ]. Nutrition transition as a result of urbanization and affluence has been considered as the major cause for the obesity epidemic [ 70 ].
Numerous literatures have documented a marked shift in the dietary pattern worldwide [ 70 , 71 ]. Major dietary changes include a higher energy density diet with a greater role for fat and added sugars in foods, greater saturated fat intake mostly from animal sources , marked increases in animal food consumption, reduced intakes of complex carbohydrates and dietary fiber, and reduced fruit and vegetable intake [ 70 — 73 ]. These dietary changes are compounded by lifestyle changes that reflect reduced physical activity at work and during leisure time [ 71 , 74 ].
Several studies have shown that insufficient physical activity is one of the important risk factors of obesity [ 75 — 77 ], and work-related activity has declined over recent decades in industrialized countries whereas leisure time dominated by television viewing and other physically inactive pastimes has increased [ 71 , 74 ]. Social inequality as a result of economic insecurity and a failing economic environment is also considered as one of the probable causes of obesity.
A review by Drewnowski [ 78 ] indicates that inequitable access to healthy foods as determined by socioeconomic factors could influence the diet and health of a population.
Energy-dense and nutrient-poor foods become the best way to provide daily calories at an affordable cost by the poor groups, whereas nutrient-rich foods and high-quality diets not only cost more but are consumed by more affluent groups. Lack of accessibility of healthy food choices [ 79 ] and the commercial driven food market environment [ 80 ] are also considered as other probable causes of obesity. The interaction effects among environmental factors, genetic predisposition and the individual behavior on excess weight gain has received research interests in recent decades. Observational evidence has shown that susceptibility to obesity is determined largely by genetic factors, but the environment prompts phenotype expression.
For instance, a study of healthy Japanese men indicated that a missense variant in the interleukin 6 receptor gene interacted significantly with dietary energy intake levels in relation to the risk of abdominal obesity [ 82 ]. Possible mechanisms by which genetic susceptibility may operate include low resting metabolic rate, low rate of lipid oxidation, low fat-free mass and poor appetite control [ 11 ]. The concept of programming in fetal or postnatal life is firstly established from experimental animal studies.
A wealth of evidence from animal studies has demonstrated that exposure to an elevated or excess nutrient supply before birth is associated with an increased risk of obesity and associated metabolic disorders in later life [ 84 ]. Results from epidemiological studies and experimental studies in human also supported that intrauterine or postnatal nutrition could predispose individuals to obesity in later life [ 84 , 85 ]. In a review by Martorell and colleagues [ 85 ], intrauterine over-nutrition as proxied by high birth weight or gestational diabetes is associated with subsequent fatness, and breastfeeding has a protective effect on the development of obesity.
In contrast, the evidence that poor nutrition in early life is a risk factor for increased fatness later in life is still inconclusive.
A public health approach to develop population-based strategies for the prevention of excess weight gain is of great importance and has been advocated in recent years [ 11 , 86 ]. The development and implementation of obesity prevention strategies should target factors contributing to obesity, should target barriers to lifestyle change at personal, environmental and socioeconomic levels, and actively involve different levels of stakeholders and other major parties. A proposed framework by Sacks [ 87 ] suggests that policy actions to the development and implementation of effective public health strategies to obesity prevention should 1 target the food environments, the physical activity environments and the broader socioeconomic environments; 2 directly influence behavior, aiming at improving eating and physical activity behaviors; and 3 support health services and clinical interventions.
Examples of policies under each of these groups are reviewed in the following sections. To alter the food environment such that healthy choices are the easier choices, and to alter the physical activity environment to facilitate higher levels of physical activities and to reduce sedentary lifestyle, are the key targets of obesity prevention policies. There are a wide range of policy areas that could influence the food environments.
Retrieved 13 October Any reproduction and use of content, videos and pictures prohibited. Many explanations have been put forth for associations between BMI and social class. These dietary changes are compounded by lifestyle changes that reflect reduced physical activity at work and during leisure time [ 71 , 74 ]. Childhood obesity Obesity hypoventilation syndrome Abdominal obesity.
These areas include fiscal food policies, mandatory nutrition panels on the formulation and reformulation of manufactured foods, implementation of food and nutrition labeling, and restricting marketing and advertising bans of unhealthy foods [ 87 — 89 ]. For instance, some studies have demonstrated that food prices have a marked influence on food-buying behavior.
A small study was done in a cafeteria setting and was designed to look at the effects of availability and price on the consumption of fruit and salad. It was shown that increasing variety and reducing price by half roughly tripled consumption of both food items, whereas returning price and availability to the original environmental conditions brought consumption back to its original levels [ 90 ]. Policy areas influencing physical activity environments include urban planning policies, transport policies and organizational policies on the provision of facilities for physical activity [ 87 , 92 ].
A recent review by Sallis and Glanz [ 93 ] summarized the impact of physical activity and food environments as solutions to the obesity epidemic. Living in walkable communities and having parks and other recreation facilities nearby were consistently associated with higher levels of physical activity in youth, adults, and older adults.
Better school design, such as including basketball hoops and having a large school grounds, and better building design, such as signs promoting stair use and more convenient access to stairs than to elevators were associated with higher levels of physical activity in youth, adults and older adults [ 93 ]. As mentioned earlier, social inequality as a result of economic insecurity and a failing economic environment is also considered as one of the probable causes of obesity [ 78 ].
Therefore, policy areas covering the financial, education, employment and social policies could impact population health. As illustrated by Sacks [ 87 ], trade agreements between countries, personal income tax regimes and social security mechanisms are some potential policy areas that could be altered at international, national and state levels for the development of population-based strategies for obesity prevention.
There are many key settings, such as schools, home environment, workplaces and community, in which policies could target to directly influence the eating and physical activity behaviors. A policy-based school intervention has been found to be effective for the prevention and control of obesity. The two-year School Nutrition Policy Initiative including components of school self-assessment, nutrition education, nutrition policy, social marketing, and parent outreach has been documented to be effective in reducing the incidence of overweight in school children [ 94 ]. A review examined the effectiveness of school-based strategies for obesity prevention and control based on results of nineteen included studies [ 95 ].
A study has evaluated the effectiveness of an intervention program, based on the Theory of Planned Behavior, on obesity indices and blood pressure in Ioannina, Greece [ 96 ]. In this study, fifth grade students were assigned to the one-year school-based intervention focused on overcoming the barriers in accessing physical activity areas, increasing the availability of fruits and vegetables and increasing parental support, and students served as control group. The intervention group also showed significantly lower BMI and blood pressure than the control group. The leadership role for schools in promoting physical activity in children and youth has also been advocated in a Scientific Statement from the American Heart Association Council [ 97 ].