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human_disease_comorbidity — Human disease comorbidity networks, Medicare (1990-1993)

Description

Networks of comorbidity between diseases, from the Human Disease Network (HuDiNe) project of Hidalgo, Blumm, Barabási and Christakis. The data were compiled from the Medicare inpatient claims (MedPAR records) of 1990 to 1993 of the elderly Americans (aged 65 or older) enrolled in Medicare and alive during the whole period: 32,341,347 hospital claims of 13,039,018 patients. Each claim lists a primary and up to nine secondary diagnoses, coded according to the ICD-9-CM classification. Nodes are diseases (ICD-9 codes), and an undirected edge connects two diseases that were diagnosed together in at least one patient, with properties giving the number of such patients and the strength of the comorbidity, measured by the relative risk and by the $\phi$-correlation (Pearson's correlation for binary variables).

Diseases are defined at two levels of resolution of the ICD-9 codes: 3 digits (the main disease categories; networks ending in _3), and up to 5 digits (the full codes, which add details to the category; networks ending in _5). For each resolution there are networks for all patients (all), and for patients of each sex (female, male), race (white, black), and their combinations (e.g. black_female). Of the 13,039,018 patients, 7,598,529 are female and 5,440,490 male, and 11,745,416 are white and 983,095 black.

The networks have the following properties:

  • name: the ICD-9-CM code of the disease (e.g. "250" or "250.00").
  • prevalence: the number of patients diagnosed with the disease in the population of the network.
  • cooccurrence (edges): the number of patients diagnosed with both diseases.
  • relative_risk (edges): the relative risk $RR_{ij} = C_{ij} N / (P_i P_j)$, where $C_{ij}$ is the co-occurrence, $P_i$ and $P_j$ the prevalences and $N$ the number of patients, i.e. the ratio between the observed co-occurrence and the one expected if the diseases were independent.
  • relative_risk_low, relative_risk_high (edges): the lower and upper limits of the 99% confidence interval of the relative risk.
  • phi (edges): the $\phi$-correlation between the two diseases.
  • t (edges): the $t$-test value of the $\phi$-correlation.

The files are obtained from the Internet Archive, the only remaining copies. Two of them are truncated there, so that their networks lack the disease pairs whose first code is larger than the last one included: white_5 ends after the pairs of code 585, and black_5 after those of code 890.1 (the incomplete last line of each file is left out).

The data are free for academic use only (according to the source, for non-academic purposes C. A. Hidalgo should be contacted).

Tags
Biological Public Health Weighted Metadata
Citation
  • C. A. Hidalgo, N. Blumm, A.-L. Barabási, N. A. Christakis, "A dynamic network approach for the study of human phenotypes." PLoS Computational Biology 5(4), e1000353 (2009) 10.1371/journal.pcbi.1000353 Sci-Hub
Upstream URL OK
https://web.archive.org/web/20101116170623/http://barabasilab.neu.edu/projects/hudine/resource/data/data.html
Upstream license
Free for academic use only, https://web.archive.org/web/20101116170623/http://barabasilab.neu.edu/projects/hudine/resource/data/data.html
Networks
Tip: click on a column header to sort the list, or hover over it for a description.
Column legend
$\left<k\right>$
Mean degree
$\sigma_k$
Standard deviation of the degrees
$\lambda_h$
Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$
Random walk mixing time
$r$
Degree assortativity
$c$
Global clustering coefficient
$\oslash$
(Pseudo-) diameter
$S$
Relative size of the largest component
NPs
Node properties
EPs
Edge properties
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv
all_3 995 291,172 585.27 272.62 699.12 0.65 -0.32 0.82 3 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 10.9 MiB 13.6 MiB 13.5 MiB 12.9 MiB
female_3 993 261,804 527.30 275.15 654.64 0.67 -0.35 0.79 3 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 9.7 MiB 12.2 MiB 12.0 MiB 11.6 MiB
male_3 972 242,056 498.06 268.96 626.91 0.67 -0.36 0.79 3 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 9.0 MiB 11.2 MiB 11.1 MiB 10.7 MiB
white_3 992 285,795 576.20 272.18 691.08 0.65 -0.33 0.82 3 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 10.7 MiB 13.3 MiB 13.2 MiB 12.6 MiB
black_3 920 186,409 405.24 245.39 530.57 0.68 -0.39 0.72 3 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 6.7 MiB 8.5 MiB 8.4 MiB 8.2 MiB
white_female_3 992 256,637 517.41 274.98 646.78 0.67 -0.36 0.79 3 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 9.5 MiB 11.9 MiB 11.8 MiB 11.3 MiB
white_male_3 964 236,513 490.69 266.19 618.28 0.67 -0.36 0.78 3 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 8.7 MiB 11.0 MiB 10.9 MiB 10.4 MiB
black_female_3 890 159,215 357.79 233.16 484.67 0.71 -0.41 0.69 3 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 5.6 MiB 7.1 MiB 7.0 MiB 6.9 MiB
black_male_3 878 142,226 323.98 224.53 451.75 0.66 -0.42 0.67 3 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 4.9 MiB 6.3 MiB 6.2 MiB 6.1 MiB
all_5 15,983 6,088,553 761.88 1367.47 2610.67 0.98 -0.48 0.43 4 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 198.2 MiB 257.1 MiB 253.2 MiB 261.0 MiB
female_5 14,506 4,882,376 673.15 1218.21 2318.81 0.97 -0.47 0.42 4 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 155.0 MiB 203.6 MiB 200.3 MiB 207.5 MiB
male_5 12,265 3,980,759 649.12 1120.80 2076.10 0.93 -0.47 0.42 4 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 123.8 MiB 164.4 MiB 161.7 MiB 168.1 MiB
white_5 15,604 4,871,245 624.36 1190.86 2261.79 1.02 -0.47 0.38 4 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 158.4 MiB 204.4 MiB 201.4 MiB 208.4 MiB
black_5 9,050 2,007,916 443.74 784.88 1424.37 1.02 -0.45 0.37 5 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 55.6 MiB 77.7 MiB 76.2 MiB 81.5 MiB
white_female_5 14,193 4,660,664 656.76 1188.57 2261.48 0.97 -0.47 0.42 4 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 147.3 MiB 193.8 MiB 190.5 MiB 197.8 MiB
white_male_5 12,026 3,775,421 627.88 1087.84 2018.53 0.92 -0.47 0.41 4 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 116.5 MiB 155.3 MiB 152.7 MiB 159.2 MiB
black_female_5 8,149 1,557,867 382.35 683.67 1245.45 0.89 -0.44 0.37 4 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 41.3 MiB 58.4 MiB 57.2 MiB 62.2 MiB
black_male_5 7,432 1,239,552 333.57 602.78 1097.27 1.13 -0.44 0.36 5 1.00 Undirected Unipartite name prevalence cooccurrence relative_risk relative_risk_low relative_risk_high phi t 31.5 MiB 44.9 MiB 43.8 MiB 48.6 MiB