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Background: The co-administration of drugs known to interact greatly impacts morbidity, mortality, and health economics. This study aims to examine the drug–drug interaction (DDI) phenomenon with a large-scale longitudinal analysis of age and gender differences found in drug administration data from three distinct healthcare systems. Methods: This study analyzes drug administrations from population-wide electronic health records in Blumenau (Brazil; 133 K individuals), Catalonia (Spain; 5.5 M individuals), and Indianapolis (USA; 264 K individuals). The stratified prevalences of DDI for multiple severity levels per patient gender and age at the time of administration are computed, and null models are used to estimate the expected impact of polypharmacy on DDI prevalence. Finally, to study actionable strategies to reduce DDI prevalence, alternative polypharmacy regimens using drugs with fewer known interactions are simulated. Results: A large prevalence of co-administration of drugs known to interact is found in all populations, affecting 12.51%, 12.12%, and 10.06% of individuals in Blumenau, Indianapolis, and Catalonia, respectively. Despite very different healthcare systems and drug availability, the increasing prevalence of DDI as patients age is very similar across all three populations and is not explained solely by higher co-administration rates in the elderly. In general, the prevalence of DDI is significantly higher in women — with the exception of men over 50 years old in Indianapolis. Finally, we show that using proton pump inhibitor alternatives to omeprazole (the drug involved in more co-administrations in Catalonia and Blumenau), the proportion of patients that are administered known DDI can be reduced by up to 21% in both Blumenau and Catalonia and 2% in Indianapolis. Conclusions: DDI administration has a high incidence in society, regardless of geographic, population, and healthcare management differences. Although DDI prevalence increases with age, our analysis points to a complex phenomenon that is much more prevalent than expected, suggesting comorbidities as key drivers of the increase. Furthermore, the gender differences observed in most age groups across populations are concerning in regard to gender equity in healthcare. Finally, our study exemplifies how electronic health records' analysis can lead to actionable interventions that significantly reduce the administration of known DDI and its associated human and economic costs. [ABSTRACT FROM AUTHOR]

Background: Multimorbidity is better prevented in younger ages than in older ages. This study aims to identify the differences in comorbidity patterns in middle-aged inpatients from China and the United Kingdom (UK). Methods: We utilized 184,133 and 180,497 baseline hospitalization records in middle-aged populations (40–59 years) from Shaanxi, China, and UK Biobank. Logistic regression was used to calculate odds ratios and P values for 43,110 unique comorbidity patterns in Chinese inpatients and 21,026 unique comorbidity patterns in UK inpatients. We included the statistically significant (P values adjusted by Bonferroni correction) and common comorbidity patterns (the pattern with prevalence > 1/10,000 in each dataset) and employed network analysis to construct multimorbidity networks and compare feature differences in multimorbidity networks for Chinese and UK inpatients, respectively. We defined hub diseases as diseases having the top 10 highest number of unique comorbidity patterns in the multimorbidity network. Results: We reported that 57.12% of Chinese inpatients had multimorbidity, substantially higher than 30.39% of UK inpatients. The complete multimorbidity network for Chinese inpatients consisted of 1367 comorbidities of 341 diseases and was 2.93 × more complex than that of 467 comorbidities of 215 diseases in the UK. In males, the complexity of the multimorbidity network in China was 2.69 × more than their UK counterparts, while the ratio was 2.63 × in females. Comorbidities associated with hub diseases represented 68.26% of comorbidity frequencies in the complete multimorbidity network in Chinese inpatients and 55.61% in UK inpatients. Essential hypertension, dyslipidemia, type 2 diabetes mellitus, and gastritis and duodenitis were the hub diseases in both populations. The Chinese inpatients consistently demonstrated a higher frequency of comorbidities related to circulatory and endocrine/nutritional/metabolic diseases. In the UK, aside from these comorbidities, comorbidities related to digestive and genitourinary diseases were also prevalent, particularly the latter among female inpatients. Conclusions: Chinese inpatients exhibit higher multimorbidity prevalence and more complex networks compared to their UK counterparts. Multimorbidity with circulatory and endocrine/nutritional/metabolic diseases among both Chinese and UK inpatients necessitates tailored surveillance, prevention, and intervention approaches. Targeted interventions for digestive and genitourinary diseases are warranted for the UK. [ABSTRACT FROM AUTHOR]

Background: Metabolic dysfunction-associated fatty liver disease (MAFLD) is a newly defined condition encompassing hepatic steatosis and metabolic dysfunction. However, the relationship between MAFLD and multi-system diseases remains unclear, and the time-dependent sequence of these diseases requires further clarification. Methods: After propensity score matching, 163,303 MAFLD subjects and 163,303 matched subjects were included in the community-based UK Biobank study. The International Classification of Diseases, Tenth Revision (ICD-10), was used to reclassify medical conditions into 490 and 16 specific causes of death. We conducted a disease trajectory analysis to map the key pathways linking MAFLD to various health conditions, providing an overview of their interconnections. Results: Participants aged 59 (51–64) years, predominantly males (62.5%), were included in the study. During the 12.9-year follow-up period, MAFLD participants were found to have a higher risk of 113 medical conditions and eight causes of death, determined through phenome-wide association analysis using Cox regression models. Temporal disease trajectories of MAFLD were established using disease pairing, revealing intermediary diseases such as asthma, diabetes, hypertension, hypothyroid conditions, tobacco abuse, diverticulosis, chronic ischemic heart disease, obesity, benign tumors, and inflammatory arthritis. These trajectories primarily resulted in acute myocardial infarction, disorders of fluid, electrolyte, and acid–base balance, infectious gastroenteritis and colitis, and functional intestinal disorders. Regarding death trajectories of MAFLD, malignant neoplasms, cardiovascular diseases, and respiratory system deaths were the main causes, and organ failure, infective disease, and internal environment disorder were the primary end-stage conditions. Disease trajectory analysis based on the level of genetic susceptibility to MAFLD yielded consistent results. Conclusions: Individuals with MAFLD have a risk of a number of different medical conditions and causes of death. Notably, these diseases and potential causes of death constitute many pathways that may be promising targets for preventing general health decline in patients with MAFLD. [ABSTRACT FROM AUTHOR]

Background: Little is known regarding life-course trajectories of important diseases. We aimed to identify diseases that were strongly associated with mortality and test temporal trajectories of these diseases before mortality.Methods: Our analysis was based on UK Biobank. Diseases were identified using questionnaires, nurses' interviews, or inpatient data. Mortality register data were used to identify mortality up to January 2021. The association between 60 individual diseases at baseline and in the life course and incident mortality was examined using Cox proportional regression models. Those diseases with great contribution to mortality were identified and disease trajectories in life course were then derived.Results: During a median follow-up of 11.8 years, 31,373 individuals (median age at death (interquartile range): 70.7 (65.3-74.8) years, 59.4% male) died of all-cause mortality (with complete data on diagnosis date of disease), with 16,237 dying with cancer and 6702 with cardiovascular disease (CVD). We identified 37 diseases including cancers and heart diseases that were associated with an increased risk of mortality independent of other diseases (hazard ratio ranged from 1.09 to 7.77). Among those who died during follow-up, 2.2% did not have a diagnosis of any disease of interest and 90.1% were diagnosed with two or more diseases in their life course. Individuals who were diagnosed with more diseases in their life course were more likely to have longer longevity. Cancer was more likely to be diagnosed following hypertension, hypercholesterolemia, CVD, or digestive disorders and more likely to be diagnosed ahead of CVD, chronic kidney disease (CKD), or digestive disorders. CVD was more likely to be diagnosed following hypertension, hypercholesterolemia, or digestive disorders and more likely to be diagnosed ahead of cancer or CKD. Hypertension was more likely to precede other diseases, and CKD was more likely to be diagnosed as the last disease before more mortality.Conclusions: There are significant interplays between cancer and CVD for mortality. Cancer and CVD were frequently clustered with hypertension, CKD, and digestive disorders with CKD highly being diagnosed as the last disease in the life course. Our findings underline the importance of health checks among middle-aged adults for the prevention of premature mortality. [ABSTRACT FROM AUTHOR]