Prevalence of Multiple Chronic Conditions Among US Adults, 2018
Open accessAbstract
This analysis provides prevalence estimates of diagnosed single and multiple (≥2) chronic conditions among the noninstitutionalized, civilian US adult population. Data from the 2018 National Health Interview Survey (NHIS) were used to estimate percentages for US adults by selected demographic characteristics. More than half (51.8%) of adults had at least 1 of 10 selected diagnosed chronic conditions (arthritis, cancer, chronic obstructive pulmonary disease, coronary heart disease, current asthma, diabetes, hepatitis, hypertension, stroke, and weak or failing kidneys), and 27.2% of US adults had multiple chronic conditions.
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The proportion of Americans with two or more chronic health conditions continues to rise.
“the proportion of Americans with two or more chronic health conditions continues to rise”
From Nurse-led approaches to address social determinants of health and advance health equity: A new framework and its implications (2023) · cites this paper as Boersma, Black, & Ward, 2020
More than a quarter (27.2%) of adults in the US have multiple chronic conditions.
“More than a quarter (27.2%) of adults in the US have multiple chronic conditions [151].”
From Toward Safer Diagnoses: A SEIPS-Based Narrative Review of Diagnostic Errors (2026) · cites this paper as [151]
The automation of simple or routine IT support functions is expected to limit job opportunities for network and computer systems administrators.
“the automation of simple or routine IT support functions is expected to limit job opportunities for network and computer systems administrators”
From Industry and occupational employment projections overview and highlights, 2023–33 (2024) · cites this paper as [55]
The Methods and Results sections examine chronic conditions among US adults, not IT employment. Searches for routine IT support automation and network and computer systems administrators found no passage addressing the claimed effect on job opportunities. (LLM, conf=0.78)
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Preprocessing to Address Bias in Healthcare Data
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Giddens, J. F., & Mullaney, S. (2023) · Journal of Professional Nursing · doi:10.1016/j.profnurs.2023.03.015 · Cited by 17 · see citing works
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Sabatello, M., Henry, S. B., Chung, W. K., Cohn, E. G., Crew, K. D., Kiryluk, K., Kukafka, R., Weng, C., & Appelbaum, P. S. (2024) · Human Genetics and Genomics Advances · doi:10.1016/j.xhgg.2024.100281 · Cited by 17 · see citing works
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Kumari, S., Bubak, M. P., Schoenberg, H. M., Davidyan, A., Elliehausen, C. J., Kuhn, K. G., VanWagoner, T. M., Karaman, R., Scofield, R. H., Miller, B. F., et al. (2021) · The Journals of Gerontology Series A · doi:10.1093/gerona/glab358 · Cited by 17 · see citing works
- Authors
- Boersma, P., Black, L. I., & Ward, B. W.
- Affiliations
- National Center for Health Statistics (US)
- Corresponding author
- Boersma, Peter
- Venue
- Preventing Chronic Disease
- Published
- 2020-09-17
- Volume
- 17
- Pages
- E106-E106
- ISSN
- 1545-1151 (ISSN-L)
- PMC
- PMC7553211
- OpenAlex
- W3087450266
- Cited by
- 702
- References
- 8
- Citations by year
- 2026: 80 · 2025: 173 · 2024: 163 · 2023: 131 · 2022: 117 · 2021: 35 · 2020: 3
- FWCI
- 51.28
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- public-domain
- Locations
- Preventing Chronic Disease (publishedVersion, public-domain)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- U.S. Department of Health and Human Services
- Centers for Disease Control and Prevention
- Topics
- Health Sciences › Medicine › Epidemiology › Chronic Disease Management Strategies
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Healthcare Policy and Management
- Keywords
- multimorbidity, chronic disease prevalence, comorbidities, arthritis, cancer, chronic obstructive pulmonary disease, coronary artery disease, asthma, diabetes mellitus, hepatitis, hypertension, stroke, kidney disease, demographic differences, United States adults
- MeSH terms
- Multiple Chronic Conditions, Adolescent, Adult, Aged, Cross-Sectional Studies, Female, Health Surveys, Humans, Male, Middle Aged, United States, Prevalence, Young Adult
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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