Take small steps, aim modestly and realistically, and then build from there. Learn more at Achieving and maintaining a healthy weight. Donate now. Home Healthy living Healthy weight Healthy weight and waist. Health seekers. Healthy waists Measuring waist circumference can help to assess obesity-related health risk.

Are you an apple or a pear? Here's how to take a proper waist measurement Clear your abdominal area of any clothing, belts or accessories. Stand upright facing a mirror with your feet shoulder-width apart and your stomach relaxed. Wrap the measuring tape around your waist. Use the borders of your hands and index fingers — not your fingertips — to find the uppermost edge of your hipbones by pressing upwards and inwards along your hip bones.

Tip: Many people mistake an easily felt part of the hipbone located toward the front of their body as the top of their hips. This part of the bone is in fact not the top of the hip bones, but by following this spot upward and back toward the sides of your body, you should be able to locate the true top of your hipbones.

Using the mirror, align the bottom edge of the measuring tape with the top of the hip bones on both sides of your body. Tip: Once located, it may help to mark the top of your hipbones with a pen or felt-tip marker in order to aid you in correctly placing the tape.

Make sure the tape is parallel to the floor and is not twisted. People are being encouraged to keep their waist measurement to less than half their height to reduce the risk of potential health problems, according to recommendations in an updated NICE draft guideline.

Using the waist-to-height ratio, in conjunction with BMI, can help to provide a practical estimate of central adiposity, which is the accumulation of fat around the abdomen, to help to assess and predict health risks, such as type 2 diabetes, hypertension or cardiovascular disease.

NICE added the waist-to-height ratio to its draft guideline after looking at evidence from several studies which showed that, alongside BMI, it could be used to assess and predict weight-related conditions in all ethnicities and sexes.

Government estimates indicate that the current costs of obesity in the UK are £6. To ensure representation of minority groups, NHANES oversamples certain populations, such as Hispanic, black, and Asian populations; low-income populations; and the elderly NHANES uses the following stages in sample selection: 1 counties or small groups of counties primary sampling units , 2 segments within sampling units, 3 households within segments, and 4 individuals within households The Institutional Review Board for the Ethics Review Board of the National Center for Health Statistics approved NHANES data collection and allowed data files to be posted on their website for public use Written informed consent was obtained from participants before collection.

We examined prevalence of obesity and abdominal obesity as outcome variables in independent analyses. Height and weight were collected in a mobile examination center by using standardized protocols.

From those measurements, we calculated BMI and rounded it to the nearest tenth. Obesity was defined as BMI at or above Waist circumference was measured with a tape measure at the uppermost lateral border of the hip crest Waist circumferences of cm or more for men and 88 cm or more for women were considered high risk and termed abdominal obesity.

Measurements of physical activity arising from work, recreation, and transportation were used to assess the effect of each on total obesity and abdominal obesity.

Vigorous activity was defined as activity that caused large heart rate or breathing increases, and moderate activity was defined as activity that caused small increases.

Transportation was defined as walking or bicycling to get to and from places. Transportation-related physical activity was dichotomized to less than 75 minutes per week versus 75 minutes or more per week.

Overall sedentary activity was assessed by asking participants to enter the total minutes each day they spent sitting in various settings: school, at home, getting to and from places, or with friends, including time spent sitting at a desk, traveling in a car or bus, reading, playing cards, watching television, or using a computer.

Responses ranged from 0 to 1, minutes per day. Three categories of daily sedentary activity were created 0 to minutes, to minutes, or minutes or more on the basis of categories used in a previous study of leisure time among US adults 17 and median statistics on time spent in sedentary activity in the United States Television viewing including watching videos and computer use were separately examined as sedentary activities.

Participants were asked to report the average hours per day in the past 30 days they spent sitting and watching television or using a computer; 6 response categories ranged from less than 1 hour to 5 hours or more. Responses for television watching or computer use variables were dichotomized to less than 2 hours a day versus 2 hours or more per day, because less than 2 hours per day of television watching is associated with gains in life expectancy Two variables related to types of meals consumed in the past 30 days were included in the model: food prepared outside the home and frozen meals or pizza consumed in the home.

Participants were asked to report the number of meals they consumed in the past 7 days that were prepared outside the home. Responses ranged from none to more than Participants were also asked to report how often they ate frozen meals or pizza at home during the past 30 days.

Responses ranged from never to times. Statistical analyses were performed by using sample weights and stratum as designed and collected by the National Center for Health Statistics for complex sampling to provide nationally representative estimates and to address oversampling, nonresponse, and noncoverage.

We used weighted analysis of variance for continuous variables and χ 2 test for categorical variables to perform univariate analysis to evaluate independent associations between population characteristics and obesity, abdominal obesity, and sex.

Models were developed for each type of physical activity, because small sample sizes precluded simultaneous inclusion of all physical activity variables. For logistic regression, physical activity, sedentary activity, and television watching or computer use variables were transformed into categorical variables according to CDC research guidelines or our defined high-risk and low-risk groups.

All logistic regression analyses were stratified by sex. Six models were created for each outcome obesity and abdominal obesity. The base model included all the demographic variables, 2 food intake variables, general sedentary activity, and television and computer use variables.

Each of the other models included the base model adjusted for each type of physical activity ie, moderate, vigorous, transportation as an independent variable. These models were constructed by adding the additional independent variable to our base model. Two-way interactions between physical activities and other characteristics eg, interaction between physical activity and obesity status for abdominal obesity model were evaluated in the weighted logistic regressions; however, because of sparsely distributed physical activity data, no valid model-fitting could be achieved with the inclusion of the interactions ie, convergence or maximum likelihood estimates could not be obtained.

Therefore, all interactions were excluded from final models. Calculations and model creations were performed by using SAS version 9. In the base model, adults who watched television 2 hours or more per day had higher odds of abdominal obesity men, OR, 1.

In the model that adjusted for moderate work-related physical activity, only men who watched television more than 2 hours a day had higher odds of abdominal obesity OR, 2. In the model that adjusted for transportation physical activity, only men who watched television 2 hours or more per day had higher odds of abdominal obesity OR, 3.

In the model that adjusted for vigorous recreational physical activity, watching television 2 hours or more per day was also associated with higher odds OR, 3.

In the model that adjusted for transportation activity, men who engaged in sedentary activity for minutes or more per day had higher odds of abdominal obesity after adjusting for transportation physical activity OR, 2.

Engaging in moderate recreational physical activity for minutes or more per week versus minutes or less was associated with reduced odds of abdominal obesity for both men OR, 0. Engaging in vigorous work-related or vigorous recreational activity was protective against abdominal obesity for men only work-related, OR, 0.

In the model that adjusted for transportation-related physical activity, an inverse association between overall sedentary activity and abdominal obesity was found among women only OR, 0. Among women, eating meals prepared away from home 3 days a week or more versus less than 3 days was associated with higher odds of obesity OR, 1.

Eating frozen meals or pizza 3 or more times a week versus less than 3 days was associated with increased odds of abdominal obesity among women OR, 3. We found no association among men between eating meals prepared away from home and obesity or abdominal obesity.

Although many types of physical activity were associated with reduced risk of obesity and abdominal obesity as our hypothesis predicted, work-based physical activity was not. Sedentary activity in general was not linked to increased risk, in opposition to our hypothesis; only excess television watching was linked to the risk of obesity and abdominal obesity.

Unhealthy meals did not increase obesity risk, in complete contrast to what we initially hypothesized.

We examined associations between obesity and abdominal obesity and types of physical activity, sedentary activity, and diet among US adults aged 20 to 64 who participated in the National Health and Nutrition Examination Survey NHANES — NHANES collects survey-based data annually to assess variables related to health and nutrition among the noninstitutionalized, civilian population of the United States To ensure representation of minority groups, NHANES oversamples certain populations, such as Hispanic, black, and Asian populations; low-income populations; and the elderly NHANES uses the following stages in sample selection: 1 counties or small groups of counties primary sampling units , 2 segments within sampling units, 3 households within segments, and 4 individuals within households The Institutional Review Board for the Ethics Review Board of the National Center for Health Statistics approved NHANES data collection and allowed data files to be posted on their website for public use Written informed consent was obtained from participants before collection.

We examined prevalence of obesity and abdominal obesity as outcome variables in independent analyses. Height and weight were collected in a mobile examination center by using standardized protocols.

From those measurements, we calculated BMI and rounded it to the nearest tenth. Obesity was defined as BMI at or above Waist circumference was measured with a tape measure at the uppermost lateral border of the hip crest Waist circumferences of cm or more for men and 88 cm or more for women were considered high risk and termed abdominal obesity.

Measurements of physical activity arising from work, recreation, and transportation were used to assess the effect of each on total obesity and abdominal obesity. Vigorous activity was defined as activity that caused large heart rate or breathing increases, and moderate activity was defined as activity that caused small increases.

Transportation was defined as walking or bicycling to get to and from places. Transportation-related physical activity was dichotomized to less than 75 minutes per week versus 75 minutes or more per week.

Overall sedentary activity was assessed by asking participants to enter the total minutes each day they spent sitting in various settings: school, at home, getting to and from places, or with friends, including time spent sitting at a desk, traveling in a car or bus, reading, playing cards, watching television, or using a computer.

Responses ranged from 0 to 1, minutes per day. Three categories of daily sedentary activity were created 0 to minutes, to minutes, or minutes or more on the basis of categories used in a previous study of leisure time among US adults 17 and median statistics on time spent in sedentary activity in the United States Television viewing including watching videos and computer use were separately examined as sedentary activities.

Participants were asked to report the average hours per day in the past 30 days they spent sitting and watching television or using a computer; 6 response categories ranged from less than 1 hour to 5 hours or more.

Responses for television watching or computer use variables were dichotomized to less than 2 hours a day versus 2 hours or more per day, because less than 2 hours per day of television watching is associated with gains in life expectancy Two variables related to types of meals consumed in the past 30 days were included in the model: food prepared outside the home and frozen meals or pizza consumed in the home.

Participants were asked to report the number of meals they consumed in the past 7 days that were prepared outside the home. Responses ranged from none to more than Participants were also asked to report how often they ate frozen meals or pizza at home during the past 30 days. Responses ranged from never to times.

Statistical analyses were performed by using sample weights and stratum as designed and collected by the National Center for Health Statistics for complex sampling to provide nationally representative estimates and to address oversampling, nonresponse, and noncoverage. We used weighted analysis of variance for continuous variables and χ 2 test for categorical variables to perform univariate analysis to evaluate independent associations between population characteristics and obesity, abdominal obesity, and sex.

Models were developed for each type of physical activity, because small sample sizes precluded simultaneous inclusion of all physical activity variables. For logistic regression, physical activity, sedentary activity, and television watching or computer use variables were transformed into categorical variables according to CDC research guidelines or our defined high-risk and low-risk groups.

All logistic regression analyses were stratified by sex. Six models were created for each outcome obesity and abdominal obesity.

The base model included all the demographic variables, 2 food intake variables, general sedentary activity, and television and computer use variables. Each of the other models included the base model adjusted for each type of physical activity ie, moderate, vigorous, transportation as an independent variable.

These models were constructed by adding the additional independent variable to our base model. Two-way interactions between physical activities and other characteristics eg, interaction between physical activity and obesity status for abdominal obesity model were evaluated in the weighted logistic regressions; however, because of sparsely distributed physical activity data, no valid model-fitting could be achieved with the inclusion of the interactions ie, convergence or maximum likelihood estimates could not be obtained.

Therefore, all interactions were excluded from final models. Calculations and model creations were performed by using SAS version 9. In the base model, adults who watched television 2 hours or more per day had higher odds of abdominal obesity men, OR, 1. In the model that adjusted for moderate work-related physical activity, only men who watched television more than 2 hours a day had higher odds of abdominal obesity OR, 2.

In the model that adjusted for transportation physical activity, only men who watched television 2 hours or more per day had higher odds of abdominal obesity OR, 3. In the model that adjusted for vigorous recreational physical activity, watching television 2 hours or more per day was also associated with higher odds OR, 3.

In the model that adjusted for transportation activity, men who engaged in sedentary activity for minutes or more per day had higher odds of abdominal obesity after adjusting for transportation physical activity OR, 2. Engaging in moderate recreational physical activity for minutes or more per week versus minutes or less was associated with reduced odds of abdominal obesity for both men OR, 0.

Engaging in vigorous work-related or vigorous recreational activity was protective against abdominal obesity for men only work-related, OR, 0. In the model that adjusted for transportation-related physical activity, an inverse association between overall sedentary activity and abdominal obesity was found among women only OR, 0.

Among women, eating meals prepared away from home 3 days a week or more versus less than 3 days was associated with higher odds of obesity OR, 1.

Eating frozen meals or pizza 3 or more times a week versus less than 3 days was associated with increased odds of abdominal obesity among women OR, 3. We found no association among men between eating meals prepared away from home and obesity or abdominal obesity.

Although many types of physical activity were associated with reduced risk of obesity and abdominal obesity as our hypothesis predicted, work-based physical activity was not. ITT Symptoms BMI and waist circumference calculator.

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News Network. Skip to main content Thank you for visiting nature. nature international journal of obesity paper article. Abstract OBJECTIVE: To examine the relationship between waist circumference and cardiovascular risk factors during weight loss, and to consider possible waist reduction targets for weight management.

Access through your institution. Buy or subscribe. Change institution. Learn more. View author publications. Rights and permissions Reprints and permissions. About this article Cite this article Han, T. Copy to clipboard. This article is cited by Effect of a six-week times restricted eating intervention on the body composition in early elderly men with overweight Przemysław Domaszewski Mariusz Konieczny Steve Anton Scientific Reports A randomized controlled trial of pharmacist-led therapeutic carbohydrate and energy restriction in type 2 diabetes Cody Durrer Sean McKelvey Jonathan P.

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