This study showed that the number of new-onset community-acquired AKI cases and IRRs gradually increased from June to July. Additionally, the subgroup analysis suggested that the point estimates for community-acquired AKI were generally highest in summer across most populations, and this trend was particularly evident in younger age groups.

Patients who developed community-acquired AKI in this study were more likely to be men, and this trend of developing AKI increased with age (Table 1). Male sex and an older age have been identified as risk factors for AKI18,19.

Most regions in Japan have distinct seasonal variations, with July through September being the hottest months of the year20. Previous studies suggested that Emergency Department visits and hospitalization due to AKI were associated with elevated ambient temperatures14 and that dehydration was a major cause of community-acquired AKI6. In this study, the risk of developing AKI gradually increased during the summer months (June–August), and the highest IRR for AKI was in July (Table 2, Supplementary Tables S4, S5). While temperature-driven dehydration is a highly plausible mechanism for this trend, notably, our findings reflect seasonal variation, and the precise underlying etiologies remain speculative. In addition to a reduction in dehydration-induced renal blood flow9,21,22, other summer-specific factors such as infectious gastroenteritis, rhabdomyolysis, or changes in physical activity may independently or jointly contribute to the observed increase in AKI incidence. Further studies integrating clinical records with regional meteorological data are warranted to clarify the relative contribution of these environmental and behavioral factors.

The subgroup analysis indicated that, while the point estimates for community-acquired AKI were generally higher in July than in February across most categories, a significant increase was not observed in all patient groups (Fig. 1, Supplementary Fig. S1). This finding suggests that, although a seasonal trend exists, the magnitude of the effect varies depending on the patients’ characteristics. Regarding sex, men and women showed a similar upward trend in July. The risk of developing AKI consistently increased in summer, even when stratified by age, and this risk was particularly high in young people (0–19 years). Heat stroke occurs more frequently in children in Japan in summer than in winter23. Severe dehydration resulting from heatstroke might be a major factor increasing the risk of community-acquired AKI in this young population. In contrast, in patients with comorbidities or those taking specific medications, the seasonal effect appeared less distinct than that in young people, with 95% CIs overlapping 1.0. This finding may be due to the relatively small number of individuals with chronic diseases or specific medication use in our study population, which consisted primarily of working-age adults. The resulting lack of statistical power in these subgroups necessitates further investigation in larger cohorts or older populations to more definitively evaluate the association between medical background and seasonality.

A strength of this study is that we showed an association between AKI and season in a non-older population, while previous reports examined the association between AKI and season in relatively older populations15,24,25,26,27. Furthermore, to the best of our knowledge, this is the first study to examine the effect of summer on the development of AKI by sex, age, and comorbidities.

This study has some limitations. First, this was an observational study. Therefore, there might have been unknown confounding factors that were not adjusted for. However, confounding factors that were likely to be influenced by seasonality in this study (e.g., hypertension, heart failure, and medication use) were considered. Consequently, we believe that other confounding factors would not have altered our results on seasonality. Second, the occurrence of AKI and comorbidities was identified by the disease name on the claims using ICD-10 codes. The data used in this study did not include laboratory data. Therefore, we were not able to identify the disease by laboratory values or by following fluctuations in these values. While previous research reported a low sensitivity (60%) but high specificity (86%) for identifying AKI by ICD-10 codes28, this may have led to an underestimation of its true incidence. Furthermore, we cannot exclude the possibility that diagnostic sensitivity varies by season. An example of this sensitivity is that increased clinical attention to dehydration or heat-related illnesses during summer might lead to more frequent coding of AKI by physicians, potentially introducing a seasonal reporting bias. We were unable to directly assess the seasonal stability of coding accuracy because of the lack of laboratory data. Therefore, our findings should be interpreted with caution. Future validation studies integrating laboratory-based clinical records are warranted to determine whether seasonal variations in coding behavior significantly affect the observed trends. Third, the JMDC claims database used in this study does not include individuals aged 75 years or older. Additionally, although the database contains some data for those aged 65–74 years, this population is underrepresented compared with the general Japanese population because of retirement and insurance transitions. Therefore, we excluded individuals aged 65 years and older from the analysis to ensure analytical stability. Consequently, our findings regarding the seasonality of AKI are specifically applicable to the working-age population younger than 65 years. Although seasonal patterns were observed even in this relatively young cohort, these results cannot be directly extrapolated to older people who are at higher risk for dehydration. Further research using databases that include older populations is necessary to confirm the effect of seasonality across all age groups. Furthermore, the JMDC database primarily comprises insured employees and their dependents, which may have introduced a “healthy worker effect.” Therefore, our study population likely represents a relatively healthier segment of the general population, excluding individuals not captured in this database who may have different risk profiles for AKI. Additionally, we could not account for occupational heat exposure, which could act as a confounder for those working in high-temperature environments. These factors should be considered when generalizing our findings to the broader population. Fourth, we might not have been able to accurately determine true community-acquired AKI. In this study, community-acquired AKI was defined as the development of AKI in patients whose claim type was outside the hospital. If the claim type was hospitalization, but AKI was the reason for hospitalization, the onset of AKI was likely to have been outside the hospital. However, completely distinguishing between these cases and AKI that developed during hospitalization is difficult. As a result, the number of community-acquired AKI cases may have been even greater than that estimated in this study. However, the purpose of this study was not to calculate the true number of patients with community-acquired AKI, but to examine the seasonality of AKI development in outpatients. Only AKI cases that were more reliably considered outpatients were considered. To address this potential diagnostic bias, we performed a sensitivity analysis restricted to strict outpatient-only cases (Supplementary Table S4) and an analysis restricted to confirmed diagnoses (Supplementary Table S5), which showed seasonal trends consistent with the primary analysis. Fifth, because this database does not include the locations where patients developed AKI, we were unable to perform a regional sensitivity analysis. Japan spans a wide climatic range from north to south, and the effect of temperature on AKI may vary by region. Although there is a consistent nationwide trend of high temperatures in summer and low temperatures in winter, our inability to account for regional climatic differences is a limitation. Future studies using databases with geographic information are necessary to clarify how regional climate variations affect the seasonality of AKI. Sixth, our study period was limited to only 2 years. Although the summer of 2018 was hotter than average29, consistent seasonal increases were observed in 2017 and 2018 (Supplementary Table S3). Nevertheless, further validation over longer periods is necessary to confirm the generalizability of these patterns. Seventh, the use of medications was identified solely on the basis of medical claims data, which presents some limitations. Information regarding over-the-counter medications was unavailable in the database. Additionally, topical medications were excluded from the analysis because their exact dates of use could not be accurately identified from the claim records. While we adjusted for major medications known to affect kidney function, the possibility of residual confounding by other drugs cannot be ruled out. Therefore, further studies are required to more comprehensively evaluate the effect of a wider range of medications on the seasonal variation of AKI.

In conclusion, this study showed that the incidence of community-acquired AKI gradually increased during the summer among working-age adults younger than 65 years in Japan. These findings highlight the potential relevance of seasonal and environmental factors in AKI prevention in outpatient settings. However, the present claims-based analysis evaluated calendar-based seasonality and did not directly assess meteorological or regional exposure data, such as temperature, humidity, heat index, individual heat exposure, or regional climatic variation. Therefore, future studies incorporating laboratory data, clinical information, and meteorological and regional exposure data are needed to clarify the role of climatic and other environmental factors in AKI incidence. Such evidence may help inform seasonally tailored strategies for AKI prevention in outpatient settings.