Previous prospective studies of community-based, non-elderly adults have described how all-cause mortality was associated with measured BMI 
, WC 
, WHtR 
, WHR 
or WTR 
. Most of the cohorts occurred in Europe, Asia or Australia. One report was a large meta-regression in which 27% of the participants came from the US, but BMI was the only indicator analyzed in that study 
. The other cited articles with US participants were earlier analyses of participants in the NHANES III examination 
; our report from the same baseline population benefits from six additional years of mortality experience.
We believe ours is the first analysis of nationally representative data to include all-cause mortality estimates associated with these five conventional adiposity indicators, and we have also included mortality estimates associated with LAP. Some of these six indicators had distinctly non-linear associations with all-cause mortality. Therefore, in order to simplify the comparison of all six indicators, we have reported categorical hazard ratios that predicted mortality for persons in each indicator’s midrange (compared to those below p25) and for persons above the indicator’s p75 (compared to those in the midrange).
Among the continuous, unadjusted adiposity indicators WTR had the strongest association with mortality, and this ranking was preserved in the multiply adjusted models. These results mirror an earlier prospective analysis of WTR and mortality in the Canadian Fitness Survey 
. Despite different anthropometric protocols, both the Canadian Fitness Survey and our NHANES analysis demonstrated that information on thigh size relative to waist size can enhance mortality prediction. These enhancements in risk estimation depended, however, on sex and whether our categorical analysis was made at adiposity boundary p25 or p75. Among men at p25, an increase in waist size alone was not significantly associated with increased mortality, but the incorporation of information about thigh size (in the denominator of WTR) substantially increased their estimated risk ( and ). We infer that the men’s increased mortality risk in the WTR midrange is not related primarily to an expanded WC but to a relatively diminished thigh circumference. As a corollary inference, men in quartile 1 of WTR are protected against mortality by their large thighs relative to their waists.
Thigh expansion among men is less common than among women, but for both sexes an increase in thigh size has been associated with reduced all-cause mortality 
. In contrast to upper-body adipose tissue, the volume of fat in the lower body tends to be less responsive to short-term variations in nutrient intake 
. The existence of metabolic benefits associated with large thighs is supported by cross-sectional studies of non-elderly adults that demonstrated larger leg-fat mass was associated with lower levels of circulating triglycerides and total cholesterol/HDL cholesterol, and higher levels of HDL-cholesterol and insulin sensitivity 
. Other benefits of an enlarged subcutaneous depot of gluteofemoral adipose tissue may include decreased circulating inflammatory cytokines, increased adiponectin, and an enhanced capacity of lower-body adipocytes to buffer or sequester fatty acids that would otherwise contribute to harmful deposition of lipid metabolites in ectopic (non-adipose) tissues 
Adults above the p75 boundary of WTR might include many persons with limited expandability of the adipose tissue in their thighs. We note with interest that black men in quartile 4 of WTR have markedly increased mortality risk, but this adverse association was not found for black women in quartile 4 ().
The reduced mortality observed among men with BMI, WC, or WHtR in the midrange relative to quartile 1 () is consistent with the previous international literature showing a J-shaped risk curve for both sexes at the lower values of these three adiposity indicators 
. Contrary to expectation, the women in our cohort tended to have increased mortality risk in adiposity midrange assessed by BMI, WC, or WHtR (), but these increased risk estimates above p25 applied specifically to non-Black women (). It is possible that some US women examined in NHANES III – primarily those non-Black – were different from women with baseline body measurements described in earlier cohorts or from other countries. The US Cancer Prevention Study II that began a decade before NHANES III reported little difference in all-cause mortality experience between white women with baseline BMI <22 kg/m2
(comparable to our BMI quartile 1) and those with BMI 22.0 to 29.9 (comparable to our BMI midrange) 
. This large, often cited cohort, however, depended on self-reported weight and height, had no objective indicator of tobacco use, excluded participants <30 years old, and underrepresented persons with low educational level. Non-elderly women in BMI quartile 1 from other environments possibly shared unfavorable nutritional or social circumstances that were associated with an increased mortality risk. By contrast, non-Black women in BMI quartile 1 from our US cohort may have included many who benefited from substantial social privilege despite having low levels of adiposity. A recent cohort reported from Mauritius has also found that women in WC quartile 1 had reduced risk of mortality if they were of South Asian ancestry (absent J-shape) but increased mortality risk if they were of African ancestry 
. Mauritian men in WC quartile 1 of either ancestry had comparably increased mortality risk.
Conventional assessments of increased adult adiposity depend on a BMI threshold value ≥30 kg/m2
(“obesity”) irrespective of age, sex or clinical circumstances 
. This threshold is close to the BMI value for p75 in our NHANES III sample of non-elderly US adults (). At this upper boundary of adiposity midrange the BMI associations with all-cause mortality (aHR 1.5 for men or women) suggest that adiposity’s impact on long-term health could have been assessed at least as well by the WC or WHtR ( and ). However, despite categorical risk estimates that were similar for BMI, WC, and WHtR at p75, the individuals located in the midrange or quartile 4 were frequently different depending on the indicator used (see the estimated prevalences of discordance in the supplementary appendix
). More recent surveys of non-elderly adults in Finland suggest that discordances between these 3 adiposity indicators may have increased since about 1997 
Given that “obese” individuals located in quartile 4 of BMI might be located in the midrange of an abdominal adiposity indicator (or vice versa
), our mortality predictions at p75 for BMI could be interpreted in conjunction with mortality predictions at the p75 values for an alternative adiposity indicator. The availability of population-based p75 values of WC or WHtR, for example, begins to respond to the American Heart Association’s request for abdominal adiposity cutoff values specific to BMI, age, and sex 
Among adults aged 18–44 years with a BMI of ~30 kg/m2
a supplementary health-risk estimate might depend on a men’s WC p75 threshold value of ~99 cm and women’s WC p75 threshold value of ~92 cm (). For adults 45–64 years old, a supplementary health-risk estimate might depend on a men’s WC p75 threshold of ~106 cm and women’s WC p75 threshold of ~103 cm. For black women, a BMI value above 30 is associated with only a weakly increased risk (aHR 1.1 [0.8–1.6]; ). Indeed, contemporary estimates from other sources suggest that the cardiometabolic risk 
and mortality risk 
for US black women begin to rise significantly only above ~33 kg/m2
. Assessing black women’s risk by the p75 WC threshold instead of the BMI threshold might better clarify their true risk. An alternative assessment for black women using the p75 threshold value for LAP instead of BMI could provide a substantially higher risk estimate (). For persons of ancestries other than non-Hispanic white, non-Hispanic black, or Mexican Americans we cannot be certain whether different adiposity thresholds would be better markers of health risk.
Similar to supplementary assessments using WC, the WHtR could likewise provide refined risk estimates for persons with BMI ~30 kg/m2
. Since the p75 for WHtR ranges from ~0.56 to ~0.64 for all non-elderly adults (), a practical, simplified estimate of health risk among persons with BMI ~30 kg/m2
could depend on rounding the WHtR p75 threshold value to 0.60 irrespective of sex and age. The same “pragmatic” WHtR threshold value has recently been proposed to identify a “Take Action” adiposity level associated with increased health risk 
Among men and women with diabetes at baseline we found that neither WC nor WHtR above p75 was associated with increased mortality risk (). Recent, large, observational studies including older participants have described a similar “obesity paradox” in which the diabetic adults with BMI ≥30, compared to the diabetic persons in lower BMI categories, had mortality risks that were reduced 
or similar 
. Compared to the risk for non-diabetic adults, the attenuation of relative risk in quartile 4 may occur because diabetes itself already carries an increased risk of mortality, and thus adiposity contributes very little further detriment to health. However, risk estimation for diabetic patients using thresholds of LAP at p75 would provide higher relative-risk estimates than those provided by WC or WHtR. Use of WTR thresholds would also yield a similarly increased relative-risk estimate, possibly because reduced thigh size is associated with an increase in circulating triglycerides 
. These advantages of LAP and WTR raise interesting issues about the pathophysiological consequences for diabetic patients of having an increased concentration of circulating triglycerides. An older cohort of high-risk patients from the US found that LAP predicted mortality better among persons without diabetes 
, whereas one from Germany found that LAP predicted mortality better among patients with diabetes 
. Our community-based US cohort cannot resolve this conflict regarding baseline diabetes status in clinic-derived cohorts.
The weak association between LAP and all-cause mortality in our cohort overall is compatible with recent reports from smaller cohorts of older adults 
. However, at the p75 boundary increased LAP predicted mortality relatively well among persons with tobacco exposure (). Among heavy smokers the concentration of circulating triglycerides is increased 
, and, since the definition of LAP extends the concept of lipid overload by including a laboratory assay of circulating triglycerides, the value of the LAP expression is closely tied to hypertriglyceridemia. Quartile 4 of LAP, therefore, likely includes an excess of heavy smokers. The increased mortality for tobacco-exposed persons above LAP p75 probably reflects their risk linked to smoking levels beyond what was captured by our binary adjustment for tobacco exposure.
The limited ability of LAP to predict mortality might be explained to some degree by LAP’s association with hepatic steatosis 
. A recent analysis of over 11,000 adult NHANES III participants reported that fatty liver (as assessed from ultrasound images of the gallbladder) had no association with increased mortality 
. This unexpected finding tends to support the recent concept that some persons with fatty livers may indeed be “good fat storers” 
who can sequester excessive lipid fuel as relatively benign triglycerides. Consistent with LAP’s relation to type 2 diabetes and similar clinical states 
, it has been proposed that triglyceride storage in liver tissue might be a marker of hepatic insulin resistance and diabetes risk, but these adverse effects of neutral triglyceride storage could be balanced by the protection it provides against lipotoxic damage to hepatocytes caused by some non-triglyceride fatty acids and their derivatives 
. In other non-adipose (ectopic) tissues there could be distinct roles for lipid storage. The functional consequences of increased intramyocellular lipid in skeletal muscle may differ depending on factors related to body fat distribution, ancestral origin, or habitual physical activity 
Our study has limitations. We measured adiposity at only one point in time, so our estimates could not account for changes in adiposity. Our models also lacked information about changes in diet, physical activity or co-morbidities that might well have modified the likelihood of mortality. In addition, our use of circumferences at the waist, hip, and thigh was limited to the NHANES’ specific anthropometric protocols. Other studies or clinical settings may employ different protocols for measuring the waist, hip, or thigh. Our analytic sample provided no genetic markers of ancestral admixture, and we included only persons who described themselves as non-Hispanic whites, non-Hispanic blacks, and Mexican-Americans. It is possible that persons of other ancestries might experience different mortality outcomes in relation to their baseline adiposity indicators. Our NHANES sample of persons with LAP values (restricted to fasting participants) underrepresented high-risk diabetic patients because insulin users were not asked to fast before their NHANES exam.
Despite these limitations, our identification of some differences in health risk associated with adiposity indicators may help to focus research questions for the future. Indeed, the concept of LAP emerged initially from an intention to estimate inexpensively how lipid metabolites were accumulated ectopically with increasing age 
. Basic research may increasingly focus on variations in the qualitative aspects and limits of lipid storage and how these characteristics may vary between tissues, regional depots, and organs. There will be complementary interests in the metabolic alterations and functional losses (“lipotoxicity”) that occur when the benign accumulation limits are exceeded 
. As new technologies describe the quantities and actions of specific fatty-acid derivatives in various anatomic locations, future epidemiologic studies may then clarify how specific regional depots of adipose tissue are related positively or negatively to lipotoxic consequences in the liver, skeletal muscle, pancreas, and other non-adipose tissues. These emerging insights should improve our ability to recognize and address health risks in population subgroups defined by sex, age, or other characteristics.