The Health, Aging, and Body Composition (Health ABC) Study—Ground-Breaking Science for 25 Years and Counting

Abstract

Background

The Health, Aging, and Body Composition Study is a longitudinal cohort study that started just over 25 years ago. This ground-breaking study tested specific hypotheses about the importance of weight, body composition, and weight-related health conditions for incident functional limitation in older adults.

Methods

Narrative review with analysis of ancillary studies, career awards, publications, and citations.

Results

Key findings of the study demonstrated the importance of body composition as a whole, both fat and lean mass, in the disablement pathway. The quality of the muscle in terms of its strength and its composition was found to be a critical feature in defining sarcopenia. Dietary patterns and especially protein intake, social factors, and cognition were found to be critical elements for functional limitation and disability. The study is highly cited and its assessments have been widely adopted in both observational studies and clinical trials. Its impact continues as a platform for collaboration and career development.

Conclusions

The Health ABC provides a knowledge base for the prevention of disability and promotion of mobility in older adults.

The Health, Aging, and Body Composition Study (Health ABC) was established in 1997 as an observational epidemiologic cohort study focused on risk factors for the decline of function in healthier older persons. Health ABC was initiated and developed in the Intramural Research in the Laboratory of Epidemiology and Population Sciences and conducted through research contracts with the Coordinating Unit at the University of California, San Francisco (UCSF), and the field centers, the University of Pittsburgh, and the University of Tennessee Health Science Center, Memphis. Its central hypothesis was that body composition change is a common pathway through which weight-related health conditions and social and behavioral factors contribute to loss of independence in old age (Figure 1).

Figure 1.

Conceptual framework for the Health, Aging and Body Composition (Health ABC) Study.

The original goal of Health ABC was to recruit equal numbers of Black and White adults as well as men and women, free of functional limitations, defined as self-report any difficulty walking ¼ mile or climbing 10 steps. Conceptually, this moved the field of study upstream to discover the early signs of functional decline. Existing measures were focused on the lower end of functioning, so Health ABC developed new measures to discriminate among better-functioning adults. The sampling strategy uniquely allowed the assessment of differences in the onset of functional limitation between older men and women as well as between Black and White adults and across a wide range of socioeconomic status.

The factors contributing to changes in body composition, including weight-related conditions, other age-related conditions, and behavioral and physiologic determinants are complex and interactive, resulting in further changes in body composition and declines in health. The design of the study with its focus on multiple health conditions, has facilitated the assessment of multimorbidity in declining function and in health care utilization. This study provided a framework to address many additional hypotheses and to add additional measures, some funded by other NIH institutes and many by investigator-initiated grants. Recent and ongoing work on genomics, metabolomics, and proteomics have leveraged its biorepository. At its core, the findings regarding body composition, sarcopenia, and obesity have been foundational for future work and have supported the design of several clinical trials. Here, we review some of the key findings and contributions of the Health ABC study. Although it is not possible to review all the findings, we focus on some of the most highly cited findings regarding physical function, body composition, nutrition, inflammation, cognition, and socioeconomic status and discuss its role in collaborative projects and as a training platform.

Health ABC Study Design

The Health ABC cohort included 3 075 men and women aged 70–79 enrolled between 1997 and 1998; 45% of the women and 33% of the men are African–American. Follow-up continued with yearly examinations for 6 years with phone calls alternating every 6 months to update functional status and health. Phone calls continued every 6 months with additional examinations at follow-up years 8 and 10. In addition, major incident health events including cardiovascular events, cancer, fractures, dementia, diabetes, and other illnesses related to hospitalizations and medical expenditures were collected from medical records and adjudicated by a committee of physicians and epidemiologists. Follow-up was extended to 16 years, ending in 2015. A National Death Index search is currently underway to update the mortality follow-up and to identify cohort members who may have reached extreme old age. All data and a biorepository of blood and urine samples have been archived at the Intramural Research Program at the National Institute on Aging (NIA).

The Health ABC clinic examination included a core set of measurements on body composition, strength, and function, with additional measurements for specific ancillary studies or to complement other measurements in the study. These materials are archived on the NIA’s website (https://healthabc.nia.nih.gov/). Numerous ancillary studies were also funded which supported novel assessments such as knee magnetic resonance imaging (MRI) for arthritis, doubly-labeled water for energy expenditure, and whole-genome genotyping.

Physical Function and Endurance

Study entry criteria required participants to be free of reported difficulty in walking ¼ mile and climbing 1 flight of stairs. We considered the incident difficulty in either of these tasks, persisting for 2 consecutive contacts to constitute the primary outcome of the study: incident functional limitation. To detect early functional change, we developed and implemented both self-report and performance-based measures of physical function that could differentiate levels of capacity at study entry and throughout follow-up and also capture the decline process comparable to existing research. These assessments included the Long Distance Corridor Walk (or fast 400 m walk), an expanded version of the Short Physical Performance Battery (Health ABC PPB), and a self-reported scale of “ease” as well as difficulty performing a range and variety of higher-order activities of daily living. These higher-order mobility assessments facilitated tracking the decline process and identifying the contribution of weight-related health conditions and social and behavioral factors (1). Several of these measures have been incorporated in subsequent studies of the aging process such as the Baltimore Longitudinal Study on Aging (2) and the Study of Mobility and Muscle Aging (3).

A key contribution has been the demonstrated utility of these more challenging tests as early markers of subclinical disease (4), vulnerability to mobility limitation (5), and cognitive decline (6). The ability to walk 400 m and the time to walk 400 m were strongly related to multiple adverse health outcomes (7). Each additional minute of 400-m performance time was associated with an adjusted HR of 1.29 (95% CI: 1.12–1.48) for mortality, 1.20 (95% CI: 1.01–1.42) for incident cardiovascular disease, 1.52 (95% CI: 1.41–1.63) for mobility limitation, and 1.52 (95% CI: 1.37–1.70) for disability after adjustment for confounders. Perera and colleagues (8) made a complementary contribution in identifying meaningful decline; that is, the amount of change significantly associated with self-reported decline in mobility in both the 400 m walk (substantial decline of about 30 seconds) and the expanded Short Physical Performance Battery (SPPB) (substantial decline of about 0.2 points out of a maximum of 4). This has facilitated their use in longitudinal investigations and clinical trials. Although aging-related decline is inevitable, numerous analyses demonstrate the age at which functional decline crosses the functional limitation/disablement threshold can be modifiable through physical activity and exercise (9–13) independent of body composition and genetic factors. Novel interventions such as senolytics (14) and anti-inflammatory drugs (15) targeting aspects of aging biology have been adopting many of these outcome assessments as well.

Body Composition

Obesity

Obesity, defined as having a Body Mass Index ≥30 kg/m², is highly prevalent among older adults and its prevalence is still increasing over time. At the baseline of the Health ABC study, about 1 out of 3 Black participants and about 1 out of 6 White participants were obese. Among women, 1 out of 3 was obese, while this was 1 out of 5 for men. Obesity was shown to be a strong risk factor for developing mobility limitation at a later age (14,15). In particular, those who were already overweight or obese at ages 25 or 50 had the poorest physical performance in old age (16) and the highest risk of developing mobility limitation (17), which underscores the importance of having a healthy body weight across the life course. Older adults with a combination of high adiposity and a low physical activity level were at the highest risk of developing mobility limitation (18). A healthy lifestyle in old age could, however, not overcome the negative impact of obesity on mobility in older adults with obesity (12). The generally observed poorer physical function in older women compared with older men could for a large part be explained by the higher fat mass of women. Also, other sex differences in body composition seemed to play a role (19).

Body Composition

A central research question of the Health ABC study is how age-related body composition changes contribute to loss of independence in old age. Total body fat mass and (appendicular) lean mass were assessed annually by dual-energy X-ray absorptiometry (DXA, Hologic QDR 4500) after conducting several validation studies (20–25) and applying standardized calibration procedures (26). In Year 1 and Year 6, 10 mm computed tomography (CT) scans were obtained at the mid-thigh level and at the waist (at the L4–L5 level) in order to measure the 5-year change in mid-thigh muscle cross-­sectional area, fat area, total abdominal fat area, and visceral fat area. Muscle attenuation was also assessed as a then-novel indicator of fat infiltration into the muscle (27).

Using the baseline data of the Health ABC study, the association between muscle cross-sectional area and muscle tissue attenuation with functional performance (6-m walk and repeated chair stands) was investigated. After adjustment for several confounders including total body fat, a smaller muscle area as well as a lower muscle attenuation—indicative of greater fat infiltration in the muscle, were associated with poorer performance (28).

To recognize the important role of total fat mass in determining physical functioning in old age, and to acknowledge the observation that older adults with a higher fat mass also have higher muscle mass, a new approach was developed to define sarcopenia. Previously, the ratio of muscle mass over height squared was commonly used, which ignores the important impact that fat mass has on muscle mass. Residuals of appendicular muscle mass, after regressing appendicular lean mass on body height and body fat mass, were associated with impaired mobility function (29). Moreover, these residuals better predicted incident mobility limitations as compared with the commonly used ratio of muscle mass over height squared (30).

Body Composition and Mortality

In terms of mortality risk, Health ABC demonstrated that both lean and fat mass contribute independently to risk, though the risk of lower lean mass can be attenuated by lower strength (31). Analysis of changes in body composition showed that older adults tended to decline in all body composition compartments except of intermuscular fat which increased over time. Losing the thigh muscle area was associated with higher mortality in both men and women and especially in those of normal weight or if the loss was greater than expected for a given overall weight loss (32). Using a compositional analysis, Farsijani showed that both lean and fat mass are important for mortality, with muscle area by CT being a stronger risk factor than lean mass by DXA but fat mass by DXA being more strongly protective than fat area by CT (33).

Muscle Strength and Quality

Using a prospective design, lower muscle cross-sectional area, lower knee extensor strength, and higher muscle tissue attenuation were all associated with a higher incidence of mobility limitations during a 2.5-year follow-up after adjustment for confounders including body height and total body fat mass, with similar associations for sex and race groups. However, when modeled together, only muscle attenuation and muscle strength remained associated with the incidence of mobility limitations (34). This study was the first to show that muscle strength and muscle composition are more important muscle parameters in determining physical functioning as compared with the amount of muscle mass.

As with the analysis of function, strength was more strongly predictive of mortality than lean mass or muscle area (31). Several papers explored the changes in muscle mass and muscle strength over time. In a very highly cited publication (Figure 2), the importance of muscle quality was further illustrated by the difference in the changes in muscle mass and muscle strength over time. Although the strongest predictor of lower extremity muscle strength was muscle size, whether measured by lean mass or muscle area, changes were not coupled over time, such that the change in strength of about 3%–4% per year was about 3 times greater than the change of lean mass of about 1% per year. Strength was lost even if lean mass increased and was greater in men and in Black participants (35).

Figure 2.

Loss of lean mass and strength in Health ABC (35). Annualized rates for declines in leg lean mass (hatched bar) and muscle strength (black bar) by gender and race. Gender difference within race, *p < .01 and racial difference within gender, †p < .05.

Nutrition

In order to investigate the role of nutrition in body composition changes and weight-related health conditions, in Year 2 of the Health ABC study a 108-item, interviewer-­administered a modified version of the Block food frequency questionnaire was used to assess energy, macro and micronutrient, and food group intake. The questionnaire was specifically developed for the Health ABC study on the basis of 24-hours recall data from the NHANES-III for older (>65 years) non-­Hispanic White and Black adults (36). In addition, markers of nutritional status were determined in blood, including serum 25-hydroxyvitamin D as a marker of vitamin D status.

Protein

As it is known that a sufficient dietary protein intake is necessary for muscle health at all ages, several Health ABC studies focused on the actual total protein intake as well as its role in the age-related changes in body composition and functional decline in older adults. A lower protein intake was frequently observed in older persons. Health ABC study data showed that the mean protein intake was 65.5 (SD 25.9) g/day, or 0.90 (SD 0.38) g/kg BW/day, with 39.2% of the cohort having an intake lower than the total protein intake recommendation of 0.8 g/kg BW/day (37). One of the landmark and highly cited studies from the Health ABC study involves the association between total protein intake and a 3-year change in lean mass and appendicular lean mass as determined by DXA (38). Participants in the highest quintile of energy-adjusted protein intake (having a median intake of 1.1 g/kg body weight/day) lost about 40% less (appendicular) lean mass than those in the lowest quintile of energy-adjusted protein intake (median 0.7 g/kg/day, see Figure 3). Strikingly, this association was not observed when a 5-year change in mid-thigh cross-sectional area as determined by CT was used to determine loss of muscle mass (39).

Figure 3.

Three-year loss of lean mass by quintile of energy-adjusted total protein intake at baseline, adjusted lean mass (LM) loss by quintile of energy-adjusted total protein intake, n = 2 066. Adjusted for age, sex, race, study site, total energy intake, baseline LM, height, smoking, alcohol use, physical activity, oral steroid use, prevalent disease (diabetes, ischemic heart disease, congestive heart failure, cerebrovascular disease, lung disease, and cancer), and interim hospitalizations. Tests for a linear trend across quintiles of protein intake were conducted by using the median value in each quintile as a continuous variable in the linear regression model; p for trend = .002. Least-squares means with different superscript letters are significantly different, p < .05 (t test). Median total protein intake as a percentage of total energy intake (g·kg⁻¹·d⁻¹) by quintile (from quintile 1 to quintile 5) was 11.2% (0.7 g·kg⁻¹·d⁻¹), 12.7% (0.7·g·kg⁻¹·d⁻¹), 14.1% (0.8 g·kg⁻¹·d⁻¹), 15.8% (0.9 g·kg⁻¹·d⁻¹), and 18.2% (1.1 g·kg⁻¹·d⁻¹), in 2 066 Health ABC study participants. Based on Houston 2008 (38).

Research in subsequent years also showed that higher protein intake was also associated with a lower risk of developing mobility limitation (40), which was confirmed in a multicohort meta-analysis in which the Health ABC study participated (41). Higher protein intake was also associated with a faster gait, and slower prospective decline in gait speed (41), but not with higher grip strength or decline in grip strength (42). These associations turned out to be similar according to the strata of physical activity, indicating that there is no need to differentiate protein intake recommendations according to physical activity levels. Some indications for sex and race differences in the associations of total protein intake with 3- and 6-year changes in gait speed and lean body mass, and with 6-year incident mobility limitations were observed (43). For some subgroups, spline functions suggested differential optimal protein intakes, suggesting that optimal protein intake may differ according to these characteristics which require further research. A lower protein intake (<0.8 g/kg of body weight/day) also increased the risk of developing (persistent) protein-energy malnutrition over time (44). This work from Health ABC shows that a lower total protein intake is highly prevalent among older adults, despite the importance of a sufficient protein intake in preventing malnutrition and in slowing down the age-related decline in muscle mass and physical functioning, informing dietary guidelines and future clinical trials.

Dietary Patterns

Using the food frequency data, several a priori dietary patterns (using a previously determined adherence index that has been linked to health outcomes) as well as posteriori dietary patterns (based on data reduction applications such as cluster analysis) have been used to examine their relationship with important outcomes, including physical functioning, frailty, and survival. A higher Mediterranean Diet score, indicative of a diet that represents the dietary patterns among populations from the Mediterranean area characterized by large quantities of olives, fruits, vegetables as salads, cooked legumes, nuts, and cereals, was consistently associated with a faster usual 20 m walk speed (45). The association was attenuated but maintained after adjustment for total body fat. The Mediterranean Diet index was however not associated with the decline in walk speed over 8 years. The association between the Healthy Eating Index (categorized as poor, medium, and good) and incident (pre-)frailty was also examined (46). Among robust and pre-frail older adults (based on the Fried criteria), those consuming poor- and medium-quality diets were 1.92 and 1.40 times more likely to develop frailty within 4 years compared with those with good-quality diets.

A posteriori dietary pattern characterized by relatively high amounts of vegetables, fruit, whole grains, poultry, fish, and low-fat dairy products was associated with better nutritional status based on nutritional biomarkers, greater insulin sensitivity, lower systemic inflammation, better quality of life, and better survival in older adults (47,48). Furthermore, this pattern was associated with a more favorable body composition (lower adiposity and mid-thigh intermuscular fat), although differential associations were reported by the PPAR-γ genotype (49).

Overall, these Health ABC studies support that an overall healthy dietary pattern in old age is not only associated with lower levels of relevant risk markers for disease but also with better physical functioning and survival.

Vitamin D

In the Health ABC cohort, the prevalence of serum 25-hydroxyvitamin D (25(OH)D) insufficiency (concentrations <30 ng/ml) was higher in Black participants (84%) compared with White participants (57%) (50). Risk factors for insufficiency were: not taking multivitamins, female gender, and obesity for Black participants, and not taking multivitamins, female gender, obesity, low dietary vitamin D intake, and having type 2 diabetes in White participants.

Participants with lower 25(OHD)D serum levels had a higher 10-year risk for major kidney function decline, but not for incident heart failure (51). They also had a poorer physical performance (lower SPPB score and slower 20 m and 400 m gait speed), but not a greater rate of decline in physical performance during 2 and 4 years of follow-up (52). Moreover, lower 25(OHD)D serum levels (<75 mnol/L vs ≥75 nmol/L) were associated with a 30%–90% higher incidence of mobility limitation and mobility disability over 6 years of follow-up (53).

Health ABC studies on the association between 25(OH)D levels and mental health show better cognitive status, slower cognitive decline, and a lower incidence of depression in those with higher levels (54,55).

Finally, in the total sample, as well as in subgroups by race, lower serum 25(OH)D concentrations were associated with a higher all-cause mortality risk over 8.5 years of follow-up (56), with population attributable risks twofold to threefold higher for Black participants compared with White participants. Interventions are now needed to investigate the causality of these associations and whether vitamin D supplementation can support active and healthy aging, apart from having beneficial effects on falls and fractures in old age.

Inflammation

Health ABC investigators recognized the potential importance of age-related inflammation early on and incorporated C-reactive protein, IL-6, and tumor necrosis factor (TNF)-alpha into the baseline examination. Inflammatory markers were higher in individuals with lower levels of physical activity (57) smoking and an obstructive pattern on lung function testing (58) and greater amounts of visceral fat, regardless of race or sex (59). Inflammatory markers were also higher in individuals with lower education, income, and assets (60), but biomedical factors only partly explained the higher risk of disability and incident mobility limitation in older adults of low social economic status (61).

In the Health ABC cohort, inflammation was associated with many aspects of poorer health including poorer physical function (62), more periodontal disease (63), and greater depressed mood (64). Together or individually, these markers predicted poorer outcomes including incident cardiovascular disease (65), heart failure (66), incident pneumonia (67), lung cancer (68), cognitive decline (69), and incident mobility limitation (70). In many cases, the number of elevated markers showed dose-response associations, however, TNF-alpha was most strongly associated with loss of muscle mass and strength (71). Together, the associations demonstrated over multiple aspects and diseases of aging support the role of inflammation as one of the hallmarks of aging (72).

Cognition and Physical Function

Although Health ABC did not emphasize cognitive function or dementia risk, it nonetheless made important contributions in this domain. Health ABC made important early insights into the relationship between cognitive and physical function. At baseline, both global cognitive function as assessed by the Modified Mini-Mental Status Exam (3MS) and executive function/processing speed as measured by the digit symbol substitution test were associated with gait speed, chair stand time, and standing balance time (6). Poor baseline cognitive performance was also associated with a faster decline in gait speed, and reciprocally, declining gait speed was associated with cognitive impairment at 14 years (73–75). The study also evaluated a number of novel risk factors for cognitive decline and incident cognitive impairment including socioeconomic disparities (76), sedentary behavior (77), aging-related biomarkers such as cystatin-c, arterial stiffness, telomere length, inflammatory markers, mitochondrial genetics, GDF-11, and GDF-8 (78–84), and other factors including hearing, diet patterns, and anemia (80,85–87).

Race/Ethnicity/SES and Literacy

A major objective of Health ABC was to examine the role of race and socioeconomic factors, including educational attainment the relationship between body composition, health-related conditions, and functional decline. Since education quality varied substantially for this cohort by geographic region, race, and possibly sex (1930s and 1940s), we also evaluated reading literacy using the Rapid Estimate of Adult Literacy in Medicine (88). Several papers document race-related disparities in outcomes ranging from health care access (89), inflammatory status (60), glycemic control in diabetics (90), cardiovascular disease (91), mobility limitation and decline (92), and mortality (93). As these studies demonstrate, even though much of the excess risk associated with Black race can be statistically explained by differences in income, assets, and/or educational attainment, some residual disparities remained.

Several other investigations of disparities in health and physical and cognitive status and decline included reading literacy as a key covariate. In most cases, accounting for low literacy reduced or eliminated race-related associations with respect to dementia (76), cognitive function test scores (94), diabetes in men only (95), and mortality (96). Although educational attainment is not modifiable, awareness of limited literacy has implications for how health- and treatment-related information is communicated to vulnerable individuals. As suggested by Sudore et al. (89), such actions may also benefit health care access another key factor in race-related health disparities (97).

Global Engagement and Consortia

The Health ABC study has been part of many international consortia. These consortia often performed meta-analysis of individual prospective cohort studies or pooled the individual participant data from different prospective cohort studies in order to increase statistical power allowing investigation heterogeneity in associations. One example is the ABI Collaboration focusing on the prediction of incident cardiovascular events using the ankle-brachial index (98). Another example is the PROMISS consortium funded by the European Union’s Horizon 2020 research and innovation program, in which meta-analysis were performed to determine the prevalence of low total protein intake in older adults (37) and individual participant data of 4 prospective cohort studies were pooled to investigate the association of total protein intake with a decline in muscle strength and walking speed, as well as the development of mobility limitations (41,42). Health ABC was a critical contributor to a highly cited paper (99) and an individual meta-analysis of the importance of gait speed as a vital sign in older adults in predicting mortality (100).

The Health ABC study was also involved in many genome-wide association meta-analyses as a member of the CHARGE consortium (101). Many phenotypes have been examined with findings including the identification of longevity genes (102), osteoporosis genes (103), and genetic associations with grip and leg strength (104). A recent meta-analysis of muscle weakness incorporating many more cohorts revealed novel pathways implicated in the biology of aging (105). The basic science of aging biology has defined many specific pathways underlying the aging process, referred to as the “Hallmarks of Aging” (72). Health ABC is contributing to this via funding for ancillary studies that leverage the biorepository.

Health ABC data have also been of critical importance to consortia related to defining sarcopenia. The Foundation for the NIH project (106) was the first data-driven approach to define sarcopenia; the Sarcopenia Definitions and Outcomes Consortium further expanded this work (107). Health ABC data and resources have also been critical to translating findings from model organisms. An example is the Comprehensive Evaluation of Aging-Related Geroproteins and Clinical Outcomes project that aimed to test whether “geroproteins” were discovered by experiments in mice using heterochronic parabiosis translated into humans using data from Health ABC and the Cardiovascular Health Study. One of the important findings from this project is that one of the proteins identified by the mouse heterochronic parabiosis studies, growth differentiation Factor 11 (GDF-11) was not associated with any mobility (108) or cognitive outcomes in humans (84).

Ancillary Studies

The Health ABC study has set the stage for a number of funded ancillary projects to expand the scope and reach of the science initially proposed. At least 28 R01s, 7 R21s, 5 R03, and numerous other awards (program projects, etc.) have been funded; some investigators have used the Health ABC to support more than 1 award. A partial list of these awards is shown in Supplementary Table 1. Some of these ancillary studies have included measurement of knee osteoarthritis with magnetic resonance imaging and a follow-up, funded by the National Institute of Arthritis and Musculoskeletal Disease and Skin Diseases, the Cognitive Vitality Substudy which focused on the maintenance of cognitive function with aging, and an energy expenditure study (funded by the National Institute of Diabetes, Digestive Disorders and Kidney Disease [NIDDK]) with a follow-up funded by NIDDK, the Centers for Disease Control and Prevention, NIA and the National Center for Mental health Disorders, in which doubly-labeled water and resting metabolic rate were used to assess level of physical activity. Repeated pulmonary function measurement was funded through an R01, and a peripheral nerve function study conducted a Year 11 assessment for the whole cohort (funded by an NIA R01). The opportunity to explore novel genetic risk factors was greatly expanded in 2009 thanks to an NIA R01 that funded whole-genome genotyping of nearly the entire cohort with subsequent exome chip genotyping for the entire cohort. An MRI of the brain and additional mobility assessment was added in a subgroup through a grant funded by an NIA K-award.

Clinical Trials

The Health ABC study has been informative in the planning of clinical trials designed to prevent disability in older adults. For example, the Lifestyle Interventions for Independence in the Elderly (LIFE) Study, developed its outcome of major mobility disability based on the Health ABC Long Distance Corridor Walk. The ENabling Reduction of Low-Grade Inflammation in Seniors Pilot Study (109) targeted levels of interleukin-6 (IL-6) found to be associated with mobility disability in Health ABC and the combined LIFE and LIFE pilot studies (110). These and other trials have relied on rates of responses to screening questions used in Health ABC to define populations at risk. Future studies could tap the Health ABC biorepository to assess new biomarkers of aging in relationship to multimorbidity and disability outcomes.

Career Awards

The Health ABC study has also served as a platform for junior scientists to launch their careers, and for established investigators to further their own mentorship or training, with 18 training or career development awards funded by NIH and many others by local institutions, foundations, or other funders (Table 1 and Supplementary Table 1).

Table 1.

NIH Funded Grant Awards that Have Leveraged the Health ABC Study

Mechanism	Grant Type	N
F31, F32	Predoctoral training awards	3
K01, K23, K24, K25	Career development awards	14
R01, R03, R21, R56, RC1, RF1, U01, P30, R13	Research grant awards	47

Publications, Citations, and Publications Network

The Health ABC study has provided a foundation of knowledge regarding the risk factors for early functional decline, especially regarding the role of body composition. Since its inception, 814 publications to date have resulted (Figure 4A) and are continuing. Citations of the study continue to be high with over 7 000 citations just in 2021 alone (Figure 4B). Although many of the publications include authors at the original study sites of NIA, UCSF, University of Pittsburgh, and University of Tennessee, Memphis, many are published by investigators at other institutions, reflecting a global extent of collaborative work (Supplementary Figure 1).

Figure 4.

Clarivate Analytics Citation Report graphic is derived from Clarivate Web of Science, Copyright Clarivate 2023; All rights reserved. (A) Number of publications from Health ABC by year. (B) Total number of citations of Health ABC publications by year.

Summary

The Health ABC study created a paradigm shift in how we had previously understood the process of aging. First, it highlighted the complexity of body composition in understanding the health and functioning of older adults, illustrating that both fat and muscle are important and that aspects of muscle quality, characterized as strength per mass and fat infiltration, are critical components of sarcopenia. The study provided evidence for targeting higher levels of function as useful outcomes in interventions on aging including nutritional and physical activity interventions. It also has shown that the importance of considering cognition and physical function together. Work on Inflammation and genetics set the stage for work on the biology of aging. Its role as a platform for so many related topics is evidenced by a large number of ancillary studies, career development grants, citations, and publications and its role in collaborative team science. Through wide access to the data and the biorepository, we expect that it will continue to serve the scientific community for many more years to come.

It is important to note that state-of-the-art methods in the 1990s have been improved upon. For example, DXA has been found to be biased and imprecise in assessing muscle mass whereas D3 creatine dilution is showing promise for next-generation studies (111). Because we focused on mobility limitation, the assessment of ADL disability and dementia was not as granular as they might have been. Genomics, metabolomics, and proteomics were anticipated and appropriate samples were saved whereas saving viable cells and tissue sampling were not achievable in Health ABC and may limit assays of interest in aging biology. Finally, Health ABC represents survivors of a birth cohort born between 1926 and 1936 who were non-mobility limited at baseline; more recent birth cohorts have had different life course experiences, calling for more follow-up of younger cohorts and initiation of new cohort studies of older adults.

Investigators interested in accessing Health ABC data and/or biorepository should contact the Intramural Research Program of the NIA via the Health ABC website: https://healthabc.nia.nih.gov/ and review the policies and procedures publication and the biorepository.

Funding

This research was supported by the National Institute on Aging (NIA) Contracts N01-AG-6-2101; N01-AG-6-2103; N01-AG-6-2106. Additional support was provided through the NIA Intramural Research Program via collaborative agreements with the National Institute of Arthritis and Musculoskeletal Disease and Skin Diseases, the National Institute of Diabetes, Digestive Disorders and Kidney Disease, the National Center for Mental health Disorders, and Centers for Disease Control and Prevention. Support from ancillary studies and career development awards are shown in Table 1 and Supplementary Table 1. A.B.N is supported by P30 AG024827 and S.B.K. by P30 AG021332.

Conflict of Interest

None.