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FNOA: Assessment of Overweight/Obesity (2012)

Citation:
 
Study Design:
Class:
- Click here for explanation of classification scheme.
Quality Rating:
Research Purpose:

To describe differences in the 22-year mortality risk associated with body mass index (BMI) body fat and fat-free mass in order to examine if the differential health consequences of fat and fat-free mass may be responsible for elevated mortality rates at both high and low BMI.

Inclusion Criteria:

A sample including all men born in 1913 on a date divisible by three and living in the city of Gothenburg in November 1972.

Exclusion Criteria:
  • Subjects from the sample who did not agree to a health examination
  • Subjects with incomplete information on total body potassium.
Description of Study Protocol:

Recruitment

Subjects were selected based on their registration number, which includes their date of birth and other vital statistics. By law, this information must be kept up to date by the County Census Bureau.

Design

Prospective cohort study. 

Statistical Analysis

  • Data were analyzed using Cox regression models
  • Measures of BMI, body fat or fat-free mass were recorded in fifths
  • A first series of models included only the risk factor
  • A second series of models included the covariate smoking habit variable
  • A third series included the covariate level of physical activity where subjects were classified as sedentary or active
  • A fourth series added first-order interactions between these variables
  • It was tested whether a continuous modeling of these variables was not significantly different from the categorical representation by comparing the likelihood of the two nested models for each variable
  • Data were returned to a continuous form for a final analysis using fractional polynomial regression to eliminate a loss of power or flawed results due to division of a continuous distribution into ordered categories. 

 

Data Collection Summary:

Timing of Measurements

All 787 men were observed from the initial examination in 1973 to December 1995. 

Dependent Variables

Mortality: Number and time of total deaths from 1973 to 1995.

Independent Variables

  • Waist circumference
  • BMI
  • Body fat and fat-free mass as measured based on total body potassium.

Control Variables

  • Current smoker, ex-smoker, non-smoker
  • Level of physical activity.

 

Description of Actual Data Sample:
  • Initial N: 787 men
  • Attrition (final N): 735 men
  • Age: 60 years old
  • Ethnicity: Swedish
  • Other relevant demographics:
    • 44% current smokers and 35% ex-smokers
    • 76% were sedentary
  • Anthropometrics: 
    • Slightly overweight with BMI of 25.5kg/m2
    • Mean percentage body fat of 30.3%
  • Location: Gothenburg, Sweden.
Summary of Results:

Key Findings

Using Cox-regression analysis, all risk functions were essentially similar before and after adjustment for baseline smoking and physical activity. Also, when including product terms, there were no interactions between either smoking or physical activity or any of the obesity mortality risk functions or between BMI, body fat or fat-free mass. In the following, only analysis adjusted for main effects of smoking and physical activity are presented.

  • Waist circumference and total mortality:
    • Independent of whether BMI was included in the model or whether waist was included as a linear or quadratic function, waist circumference was not statistically associated with total mortality
    • The highest risk was observed for men in the highest fifth of waist circumference with RR=1.2 (95% CI: 0.9 to 1.6 compared with men belonging to the lowest fifth of waist circumference)
  • Percentage body fat and total mortality:
    • The highest risk was observed for men in the highest fifth of percentage body fat with a significantly increased RR=1.5 (95% CI: 1.11 to 2), compared with men belonging to the lowest fifth percentage body fat
    • The risk function of percentage body fat mass and total mortality was comparable with linearity (chi-square test = 3.6, P=0.31)
  • BMI and total mortality:
    • The lowest risk was observed for men belonging to the middle fifth of BMI. The highest risk was observed for the men in the highest fifth of BMI and this risk was not significantly different from that risk associated with the lowest fifth of BMI (P=0.29)
    • This showed a U-shaped association between BMI and mortality. The U-shaped association was confirmed in an additional analysis in which the term BMI2 was included and found to be significant (P=0.02)
    • When the relative risk was set at one for subjects belonging to the middle fifth of BMI, the risk associated with the lowest BMI fifth was 1.3 (95% CI: 0.94 to 1.68) and that associated with the highest fifth was 1.5 (95% CI: 1.09 to 1.96)
  • Body composition, BMI and total mortality:
    • In a fifth set of models, fat-free mass and body fat were included to predict total mortality
    • From these analysis, there was no evidence of a lower limit for body fat below which total mortality risk was increased (linearity test: Chi-square=3.2, P=0.36)
    • For fat-free mass, men belonging to the lowest fifth generally had a higher total morality risk than men from higher fifths where mortality risk did not differ (linearity test: Chi-square=4.5, P=0.21)
    • Expressing body fat and fat-free mass as fractions of BMI as proposed by VanItalie et al gave similar results and suggested a lower absolute limit corresponding to the upper range for height-adjusted fat-free mass in the lowest fifth, of 16kg/m2. 
    • Fractional polynomial regression analysis, including either body fat or fat-free mass confirmed the categorical analysis.
Author Conclusion:
  • This present study shows that the apparent U-shaped association between BMI and total mortality may be a result of compound risk functions from body fat and fat-free mass. This study demonstrates that percentage fat and fat-free mass are a positive and a negative linear function of mortality, respectively. 
  • It is apparent that misclassifications with respect to obesity occur when BMI is used as a proxy variable for body fat.  This study demonstrated the different morality risk functions described by overweight, using BMI and by body composition using fat or fat-free mass. It was also shown that the use of body composition measures offer a more plausible explanation regarding the association between adiposity and mortality than that found for BMI. It is well recognized that at the high end of BMI muscular subjects may well be misclassified as overweight when they are lean. However, less than half of the subjects with low BMI (66 of 147) were actually lean in terms of body fat. This is in agreement with other studies that show the sensitivity of classifying a high body fat mass from a high BMI may be as low as 20% to 50%. A low sensitivity has been reported, particularly among older subjects. 
  • This study has also shown that body fat and fat-free mass, but not BMI, may be used to rank individuals with respect to total mortality risk. In this regard, a high percentage body fat was significantly associated with a 40% increase in total mortality compared with a low percentage body fat. The corresponding figure of 20% for BMI was not significant. This is in agreement with other studies.
  • The American Institute of Nutrition Committee on Healthy Weight concluded that the lowest risk associated with BMI was in the 18 to 23kg/m2 range. They also noted that adults with a BMI of less than 18 may be fit and healthily, but have minimal reserve in the event of an unrelated illness. A BMI of less than 16 may be an indicator of an eating disorder or underlying illness. In this study, where both body fat and fat-free mass were expressed as functions of body weight, it was found that total mortality was a linear function of body fat mass, which suggests that there is no lower critical fat mass below which total mortality is increased. For fat-free mass, it appeared in this study that a certain fat free mass was critical. In this study that mass was critical when subject's  fat-free mass/height2 and hence their BMI was less than 16 kg/m2. 
  • The present study underscores the importance of understanding the nature of how body fatness varies with BMI in order to fully understand the health risks associated with obesity. The u-shaped association between overweight and total mortality may be a result of differential health consequences for body fat and fat free mass and compared with low levels, a high fat mass is more strongly associated with mortality risk than BMI.  These findings have implications for the understanding of obesity/mortality relations and for further public health recommendations.
Funding Source:
Government: Swedish Medical Research Council, the Danish National Research Foundation, the Danish Health Insurance Foundation
Not-for-profit
King Gustaf V and Queen Victoria's Foundation, the Gothenburg Medical Association, the Danish Heart Association
Foundation associated with industry:
Reviewer Comments:

The authors note the following limitations:

  • Differences dependent upon gender could not be examined in this study because only men were studied
  • Relatively small sample size
  • Previous studies have found associations with mortality and waist-to-hip ratio. This was not examined here because only a measurement of waist, not hip circumference, were performed.
  • It should be noted that compared with other methods like underwater weighing or indicator dilution, fat-free mass may be underestimated in obese or elderly by potassium counting.
Quality Criteria Checklist: Primary Research
Relevance Questions
  1. Would implementing the studied intervention or procedure (if found successful) result in improved outcomes for the patients/clients/population group? (Not Applicable for some epidemiological studies) N/A
  2. Did the authors study an outcome (dependent variable) or topic that the patients/clients/population group would care about? Yes
  3. Is the focus of the intervention or procedure (independent variable) or topic of study a common issue of concern to dieteticspractice? Yes
  4. Is the intervention or procedure feasible? (NA for some epidemiological studies) N/A
 
Validity Questions
1. Was the research question clearly stated? Yes
  1.1. Was (were) the specific intervention(s) or procedure(s) [independent variable(s)] identified? Yes
  1.2. Was (were) the outcome(s) [dependent variable(s)] clearly indicated? Yes
  1.3. Were the target population and setting specified? Yes
2. Was the selection of study subjects/patients free from bias? ???
  2.1. Were inclusion/exclusion criteria specified (e.g., risk, point in disease progression, diagnostic or prognosis criteria), and with sufficient detail and without omitting criteria critical to the study? Yes
  2.2. Were criteria applied equally to all study groups? Yes
  2.3. Were health, demographics, and other characteristics of subjects described? Yes
  2.4. Were the subjects/patients a representative sample of the relevant population? No
3. Were study groups comparable? N/A
  3.1. Was the method of assigning subjects/patients to groups described and unbiased? (Method of randomization identified if RCT) N/A
  3.2. Were distribution of disease status, prognostic factors, and other factors (e.g., demographics) similar across study groups at baseline? N/A
  3.3. Were concurrent controls or comparisons used? (Concurrent preferred over historical control or comparison groups.) N/A
  3.4. If cohort study or cross-sectional study, were groups comparable on important confounding factors and/or were preexisting differences accounted for by using appropriate adjustments in statistical analysis? N/A
  3.5. If case control study, were potential confounding factors comparable for cases and controls? (If case series or trial with subjects serving as own control, this criterion is not applicable.) N/A
  3.6. If diagnostic test, was there an independent blind comparison with an appropriate reference standard (e.g., "gold standard")? N/A
4. Was method of handling withdrawals described? Yes
  4.1. Were follow-up methods described and the same for all groups? Yes
  4.2. Was the number, characteristics of withdrawals (i.e., dropouts, lost to follow up, attrition rate) and/or response rate (cross-sectional studies) described for each group? (Follow up goal for a strong study is 80%.) Yes
  4.3. Were all enrolled subjects/patients (in the original sample) accounted for? Yes
  4.4. Were reasons for withdrawals similar across groups? Yes
  4.5. If diagnostic test, was decision to perform reference test not dependent on results of test under study? N/A
5. Was blinding used to prevent introduction of bias? No
  5.1. In intervention study, were subjects, clinicians/practitioners, and investigators blinded to treatment group, as appropriate? N/A
  5.2. Were data collectors blinded for outcomes assessment? (If outcome is measured using an objective test, such as a lab value, this criterion is assumed to be met.) No
  5.3. In cohort study or cross-sectional study, were measurements of outcomes and risk factors blinded? No
  5.4. In case control study, was case definition explicit and case ascertainment not influenced by exposure status? N/A
  5.5. In diagnostic study, were test results blinded to patient history and other test results? N/A
6. Were intervention/therapeutic regimens/exposure factor or procedure and any comparison(s) described in detail? Were interveningfactors described? Yes
  6.1. In RCT or other intervention trial, were protocols described for all regimens studied? N/A
  6.2. In observational study, were interventions, study settings, and clinicians/provider described? N/A
  6.3. Was the intensity and duration of the intervention or exposure factor sufficient to produce a meaningful effect? Yes
  6.4. Was the amount of exposure and, if relevant, subject/patient compliance measured? N/A
  6.5. Were co-interventions (e.g., ancillary treatments, other therapies) described? N/A
  6.6. Were extra or unplanned treatments described? Yes
  6.7. Was the information for 6.4, 6.5, and 6.6 assessed the same way for all groups? N/A
  6.8. In diagnostic study, were details of test administration and replication sufficient? N/A
7. Were outcomes clearly defined and the measurements valid and reliable? Yes
  7.1. Were primary and secondary endpoints described and relevant to the question? Yes
  7.2. Were nutrition measures appropriate to question and outcomes of concern? Yes
  7.3. Was the period of follow-up long enough for important outcome(s) to occur? Yes
  7.4. Were the observations and measurements based on standard, valid, and reliable data collection instruments/tests/procedures? Yes
  7.5. Was the measurement of effect at an appropriate level of precision? Yes
  7.6. Were other factors accounted for (measured) that could affect outcomes? Yes
  7.7. Were the measurements conducted consistently across groups? Yes
8. Was the statistical analysis appropriate for the study design and type of outcome indicators? Yes
  8.1. Were statistical analyses adequately described and the results reported appropriately? Yes
  8.2. Were correct statistical tests used and assumptions of test not violated? Yes
  8.3. Were statistics reported with levels of significance and/or confidence intervals? Yes
  8.4. Was "intent to treat" analysis of outcomes done (and as appropriate, was there an analysis of outcomes for those maximally exposed or a dose-response analysis)? N/A
  8.5. Were adequate adjustments made for effects of confounding factors that might have affected the outcomes (e.g., multivariate analyses)? Yes
  8.6. Was clinical significance as well as statistical significance reported? Yes
  8.7. If negative findings, was a power calculation reported to address type 2 error? N/A
9. Are conclusions supported by results with biases and limitations taken into consideration? Yes
  9.1. Is there a discussion of findings? Yes
  9.2. Are biases and study limitations identified and discussed? Yes
10. Is bias due to study's funding or sponsorship unlikely? Yes
  10.1. Were sources of funding and investigators' affiliations described? Yes
  10.2. Was the study free from apparent conflict of interest? Yes