Dashboard With Bump Charts to Visualize the Changes in the Rankings of Leading Causes of Death According to Two Lists: National Population-Based Time-Series Cross-Sectional Study
Notice bibliographique
Résumé
BACKGROUND: Health advocates and the media often use the rankings of the leading causes of death (CODs) to draw attention to health issues with relatively high mortality burdens in a population. The National Center for Health Statistics (NCHS) publishes "Deaths: leading causes" annually. The ranking list used by the NCHS and statistical offices in several countries includes broad categories such as cancer, heart disease, and accidents. However, the list used by the World Health Organization (WHO) subdivides broad categories (17 for cancer, 8 for heart disease, and 6 for accidents) and classifies Alzheimer disease and related dementias and hypertensive diseases more comprehensively compared to the NCHS list. Regarding the data visualization of the rankings of leading CODs, the bar chart is the most commonly used graph; nevertheless, bar charts may not effectively reveal the changes in the rankings over time. OBJECTIVE: The aim of this study is to use a dashboard with bump charts to visualize the changes in the rankings of the leading CODs in the United States by sex and age from 1999 to 2021, according to 2 lists (NCHS vs WHO). METHODS: Data on the number of deaths in each category from each list for each year were obtained from the Wide-ranging Online Data for Epidemiologic Research system, maintained by the Center for Disease Control and Prevention. Rankings were based on the absolute number of deaths. The dashboard enables users to filter by list (NCHS or WHO) and demographic characteristics (sex and age) and highlight a particular COD. RESULTS: Several CODs that were only on the WHO list, including brain, breast, colon, hematopoietic, lung, pancreas, prostate, and uterus cancer (all classified as cancer on the NCHS list); unintentional transport injury; poisoning; drowning; and falls (all classified as accidents on the NCHS list), were among the 10 leading CODs in several sex and age subgroups. In contrast, several CODs that appeared among the 10 leading CODs according to the NCHS list, such as pneumonia, kidney disease, cirrhosis, and sepsis, were excluded from the 10 leading CODs if the WHO list was used. The rank of Alzheimer disease and related dementias and hypertensive diseases according to the WHO list was higher than their ranks according to the NCHS list. A marked increase in the ranking of unintentional poisoning among men aged 45-64 years was noted from 2008 to 2021. CONCLUSIONS: A dashboard with bump charts can be used to improve the visualization of the changes in the rankings of leading CODs according to the WHO and NCHS lists as well as demographic characteristics; the visualization can help users make informed decisions regarding the most appropriate ranking list for their needs.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».