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. 2026 Feb 16;16:9256. doi: 10.1038/s41598-026-39558-5

Chronic PM2.5 exposure and increased risk of hospitalization for kidney disease in São Paulo, Brazil

Iara Da Silva 1,2,3, Mario Eduardo Gavidia Calderón 1, Alejandro D Peralta 1, Igor Smolentzov 2, Caroline F H Wikuats 1, Joris J T H Roelofs 4,5, Sandrine Florquin 4, Talita Rojas Sanches 2, Edmilson D Freitas 1, Jesper Kers 4,5,6, Alessandra Tammaro 4,5, Maria de Fatima Andrade 1, Lucia Andrade 2,✉
PMCID: PMC13000325  PMID: 41699102

Abstract

Exposure to fine particulate matter (PM2.5) has been associated with an increased risk of chronic kidney disease (CKD), and exposure to PM2.5 is known to aggravate ischemia/reperfusion injury-induced acute kidney injury (AKI) in mice. The impact of PM2.5 concentration on the incidence of CKD, AKI, and glomerulopathy in the megacity of Sao Paulo is has never been described. We analyzed meteorological variables, PM2.5 concentrations, and hospital admissions in São Paulo, Brazil, from 2011 to 2021. Admissions were categorized by age and sex. We analyzed 37,170 records, 55% representing males. Exposure to PM2.5 was found to increase CKD hospitalization risk by 1–4 times (95% CI: 1.009–1.18), across different age groups and exposure levels. Long-term exposure to a high PM2.5 concentration (65 μg/m3) increases that risk considerably for individuals aged 19–50 years (relative risk [RR]: 1.01; 95% CI: 1.005–1.015 and RR: 1.013; 95% CI: 1.01–1.018, respectively), the risk being ≤ 2.5 times higher in men aged 51–75 years (RR: 1.025; 95% CI: 1.015–1.032). The AKI hospitalization risk after prolonged exposure to high PM2.5 concentrations was highest for men aged 19–50 years (RR: 1.04; 95% CI: 1.012–1.07). The risk of glomerulopathy was highest in the < 40-year age group, especially among men exposed to concentrations of 15 μg/m3 (RR: 1.02; 95% CI: 1.007–1.025) and 65 μg/m3 (RR: 1.07; 95% CI: 1.02–1.11). Such exposure also increased the cumulative risk of hospitalization for membranous nephropathy, regardless of sex and age. Our findings underscore the urgent need to develop global strategies for air pollution reduction.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-026-39558-5.

Keywords: Air pollution, Kidney disease, Chronic kidney disease, Acute kidney injury, Glomerulopathy, Hospitalization

Subject terms: Diseases, Environmental sciences, Medical research, Nephrology, Risk factors

Introduction

Air pollution is a critical global health issue that has been linked to a range of conditions, including pulmonary, cardiovascular, and renal diseases1–3. It is also associated with complications such as preterm birth, low birth weight, and cognitive deficits4. This problem is particularly acute in megacities, where elevated concentrations of gases and particles are often registered5,6. The city of São Paulo, Brazil, the largest megacity in South America, with a population exceeding 12 million7, faces severe air quality challenges due to disorganized urbanization and increasing numbers of air pollution sources. In the city, levels of regulated pollutants frequently exceed established air quality standards8. The Companhia Ambiental do Estado de São Paulo (CETESB, São Paulo State Environmental Protection Agency) identifies fine particulate matter with an aerodynamic diameter ≤ 2.5 µm (PM2.5) as a major concern, with concentrations often surpassing the 50 µg/m3 daily average standard established by CETESB9. The World Health Organization (WHO) recommends a 24-h exposure limit of 15 µg/m310.

There is epidemiological evidence that long-term exposure to PM2.5 is associated with an increased risk of chronic kidney disease (CKD) development, CKD progression, albuminuria, stage 5 CKD, adverse post-transplant outcomes, and glomerular diseases3,11–14. Recently, Troost et al.15 demonstrated that exposure to air pollutants at high concentrations accelerates primary glomerular disease progression. Animal studies have shown that PM2.5 exposure induces the production of autoantibodies and immune complexes, resulting in immune dysregulation16,17, which is implicated in the pathogenesis of some glomerular diseases. Exposure to PM2.5 can also induce oxidative stress, which upregulates PLA2R expression in the lung and is involved in the pathogenesis of membranous nephropathy18. Worldwide, renal diseases have become a considerable health burden19. It is estimated that a substantial proportion of the Brazilian population has had or will have CKD (diagnosed or undiagnosed): 9.7% of the overall population in 2022 and 10.7% in 202720. This growing prevalence represents a major public health challenge, with expenditures for renal dialysis placing a substantial burden on the public health care system. Our recent research indicates that PM2.5 exposure aggravates ischemia/reperfusion-induced acute kidney injury (AKI) and may play a role in its progression by accelerating molecular aging mechanisms21.

In view of the considerations outlined above, the aim of this study was to investigate the relationship between cumulative exposure to PM2.5 and hospitalization for kidney disease in the city of São Paulo from 2011 to 2021. We also explore variations in these relationships by sex, distinct age group, and specific renal disease category (AKI, CKD, glomerular diseases, and membranous glomerulopathy).

Methods

Study area

In addition to being the largest metropolis in South America, the city of São Paulo serves as an important socioeconomic and cultural center. With its high population density and diverse economic/administrative activities, the city of São Paulo faces significant challenges regarding air quality. The city is among the most polluted in Brazil, with particularly high concentrations of pollutants such as PM2.5, which pose health risks to its residents. Air pollution levels in the city frequently exceed the limits recommended by the WHO, especially for surface ozone and PM2.522. The city has a fleet of approximately seven million vehicles9, which impacts its air quality due to the emissions of various pollutants. Air quality data (24-h averages) showed that PM2.5 concentrations were in the 50–75 µg/m3 range on 8% of days in 20219. The main source of PM2.5 is vehicle emissions5.

Data collection

Meteorological and air quality data were collected from eight monitoring stations operated by CETESB (Localized in São Paulo city – Fig. 2). The variables under analysis included daily average temperatures (°C), relative humidity (%), and PM2.5 concentrations (µg/m3), as shown in Supplementary Figure S1. To ensure comprehensive coverage, data from all monitoring stations within the city were aggregated and averaged. These city-level mean values were assigned as individual exposure estimates for all residents. Although this strategy ensures broad spatial coverage, it may result in some degree of exposure misclassification due to unaccounted intra-city variability. Other air pollutants were not included due to their high correlation with PM2.5, which was chosen as the primary exposure given its relevance and persistent concentrations in São Paulo despite emission control policies.

Fig. 2.

Fig. 2

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Spatial interpolation of the average fine particulate matter (PM₂.₅) concentration over the 10-year study period, using the deterministic inverse distance weighting method, which weights measured values according to their distance from the air quality monitoring stations. The spatial interpolation and map visualization were performed using Python (version 3.7).

The health data encompassed daily hospital admission counts from 2011 to 2021 for residents of the city of São Paulo. These records were sourced from both public and private health care systems affiliated with the Brazilian Sistema Único de Saúde (SUS, Unified Health Care System). The hospital admission data are publicly available via the online platform of the SUS Information Technology Department23.

Patients investigated in the study had been diagnosed with diseases directly or indirectly related to kidney conditions, identified by using specific codes from the International Classification of Diseases, 10th Revision (ICD-10). The codes covered a range of conditions (Supplementary Table S1). Initially, all cases were analyzed together. However, to refine the analysis, ICD-10 codes were later categorized into three main groups: AKI; CKD (all stages, including chronic dialysis); and glomerular diseases and membranous nephropathy. Daily hospital admission data were stratified by patient age group: ≤ 18, 19–50, 51–75, and > 75 years for AKI and CKD; and ≤ 40 and > 40 years for glomerular diseases. The data were also stratified by sex.

Ethical aspects of using public health data

This study was conducted in accordance with applicable data protection and privacy regulations. No personally identifiable information was collected, accessed, or disclosed. The procedures followed were in compliance with institutional ethical standards and with the principles outlined in the Declaration of Helsinki.

According to Resolution No. 510/2016 of the Brazilian National Health Council, research using publicly accessible information, as defined by the Access to Information Law (Law No. 12,527/2011), and conducted in accordance with ethical principles, is exempt from review by Research Ethics Committees (CEPs).

Statistical analysis

A regression analysis employing the generalized additive model (GAM)24, combined with negative binomial exponential probability distribution, was conducted in a time-series study25. We examined temperature, relative humidity, and PM2.5 concentrations for each group. Two additional variables were included in the model: “holiday”, represented as 0 for non-holidays and 1 for national holidays; and “weekday”, represented as 1 for Sunday, 2 for Monday, and so forth. These variables were introduced to account for the trend of weekday hospital admission, as reported in previous studies26 and observed in the database analyzed. Four degrees of freedom (df) were considered for the smooth functions.

In the present study, the medians of each independent variable were used as reference values. The cross-basis of these indicators was modeled using natural cubic splines for the variable and lagged dimensions. Given the nonlinear effects of exposure to PM2.5, we assessed the cumulative impact of medium-duration exposure, defined as 2,000 days. The R package for distributed lag linear and distributed lag non-linear models provides a framework that simultaneously accounts for exposure–response and time-delay effects27. When combined with the GAM, this package allows the creation of risk curves by providing lagged event values for up to 2,000 days for all groups. Risk indicates how much more or less likely the outcome is to occur in the exposed group in comparison with the unexposed group28,29. The relative risk (RR) is the ratio of incidence among the exposed versus the unexposed30. When assessing the relationship between exposure and health outcomes through regression analysis, we used regression coefficients (β values) for each explanatory variable. The RR value indicates how much exposure increases the risk of hospitalization within each disease group analyzed. Finally, we plotted survival curves, for the sample as a whole and for each sex, using Kaplan–Meier curves to illustrate changes in the probability of in-hospital survival over the length of hospital stay, where time was defined as the duration of hospitalization and the event as in-hospital mortality.

Results

During the 10-year study period, 37,166 hospital admissions were analyzed. Table 1 presents the data categorized by sex, age, and disease group (AKI, CKD, and glomerular diseases). Most of the cases were in males. The prevalence of AKI and CKD was higher in the older age groups, whereas glomerular disease was more prevalent among younger individuals. Figure 1 illustrates that hospital admissions for kidney diseases were concentrated in the more urbanized areas of the city. Figure 2 presents a map of PM2.5 concentrations in the city of São Paulo.

Table 1.

Number of hospital admissions registered during the study period, by disease group, sex, and age.

Males Females
Age AKI CKD Age GD Age AKI CKD Age GD
(years) (n) (n) (years) (n) (years) (n) (n) (years) (n)
0–18 468 867 0–40 2,961 0–18 333 635 0–40 2,710
19–50 1,578 3,227 19–50 1,113 2,969
51–75 2,695 3,765  > 40 1,207 51–75 1,947 3,317  > 40 790
 > 75 1,513 2,079  > 75 1,257 1,739
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AKI, acute kidney injury; CKD, chronic kidney disease; GD: glomerular disease.

Fig. 1.

Fig. 1

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(a) Location of the study area showing the spatial distribution of hospital admissions for kidney disease in the city of São Paulo; (b) Spatial distribution of hospital admissions for acute kidney injury (AKI), chronic kidney disease (CKD), and glomerular disease (GD). Maps were generated using Python (version 3.7).

Figure 3 presents a contour graph of the cumulative exposure to PM2.5 over 5 years, by age group. Males and females in the 0–18 age group exhibited an increase in RR with higher PM2.5 concentrations. That risk was particularly pronounced at certain lag times, indicating that younger populations are highly sensitive to PM2.5 exposure. The RR trends were lower in adults aged 19–50 than in the younger populations. However, higher PM2.5 levels still correspond to an increased risk in that age group, although the sensitivity to lag time is less pronounced.

Fig. 3.

Fig. 3

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Contour graph of cumulative exposure to fine particulate matter (PM2.5) based on the pollutant profile and a 2,000-day lag for all studied diseases, categorized by age and gender.

For middle-aged adults (51–75 years of age), the variability in risk was more significant, particularly concerning lag time. Higher PM2.5 concentrations were associated with increased risk, although the timing of exposure also plays a crucial role in determining health outcomes. Finally, at higher PM2.5 concentrations and longer lag times, the RR was notably higher in men > 75 years of age than in males in other age groups, suggesting that elderly males are particularly vulnerable to PM2.5 exposure. For females, the risk increase with age was more subtle but still evident, especially at higher PM2.5 levels and extended lag times.

Figure 4 presents Kaplan–Meier curves of survival probability after hospitalization for kidney disease. As expected, the probability of survival decreases as the length of hospital stay increases. For females, this probability stabilizes after 110 days of hospitalization. However, for males, the probability continues to decline until the maximum recorded duration of the hospital stay is reached.

Fig. 4.

Fig. 4

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Kaplan–Meier curve showing in-hospital survival as a function of length of hospital stay for kidney diseases: (a) Sample as a whole; (b) Males; (c) Females. (Dashed lines indicate the 95% confidence interval).

Exposure–response curves of cumulative relative risk related to hospitalization for AKI

The exposure–response curves show the cumulative risk associated with hospital admission for AKI and exposure to PM2.5 at specific concentrations. We analyzed two different concentrations of PM2.5, over time (Fig. 5) and overall (Table 2): 15 µg/m3, which represents the median in our study and aligns with the WHO recommended limit; and 65 µg/m3, the highest value registered in our study. Men start to present an increased risk for AKI-related hospital admission after approximately 1,500 days of exposure, with the risk being greater at the higher PM2.5 concentration (Fig. 5a–d). Notably, even at a concentration of 15 µg/m3, there was still a measurable risk. The cumulative risk was higher for males in the ≤ 18-year and 19- to 50-year age groups than for those in the 51- to 75-year and > 75-year age groups. The relative risk did not increase for men aged > 75 years (Fig. 5d). Figure 5 also presents the cumulative risk of hospital admission for AKI in females, associated with exposure to PM2.5 at the two specific PM2.5 concentrations across age groups. It is noteworthy that there was no cumulative risk of hospital admission for AKI observed for females of any age at either PM2.5 concentration (Fig. 5e–h).

Fig. 5.

Fig. 5

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(a–d) Exposure–response curves showing the cumulative relative risk for hospitalization due to acute kidney injury at different concentrations of fine particulate matter in various age groups of males. The gray shading represents the 95% confidence interval. (e–h) Exposure–response curves showing the cumulative relative risk for hospitalizations due to acute kidney injury at different concentrations of fine particulate matter in various age groups of females. The gray shading represents the 95% confidence interval.

Table 2.

Relative risk of hospitalization for acute kidney injury and chronic kidney disease over 2,000 days of exposure to 65 µg/m3 of fine particulate matter, by sex and age.

Age Hospitalization for AKI Hospitalization for CKD
Males Females Males Females
(years) RR (95% CI) RR (95% CI) RR (95% CI) RR (95% CI)
0–18 1.06 (1.00–1.12) 1.025 (0.96–1.101) 1.039 (0.999–1.08) 0.98 (0.94–1.036)
19–50 1.043 (1.018–1.07) 0.984 (0.964–1.025) 1.01 (0.988–1.025) 1.041 (1.028–1.06)
51–75 1.012 (0.986–1.029) 1.013 (0.976–1.03) 1.025 (1.012–1.035) 1.03 (1.015–1.041)
 > 75 0.98 (0.965–1.018) 0.99 (0.967–1.023) 1.025 (1.001–1.042) 0.973 (0.96–1.011)
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AKI, acute kidney injury; CKD, chronic kidney disease; RR, relative risk.

Exposure–response curves of cumulative relative risk related to hospitalization for CKD

At either PM2.5 concentration (15 or 65 µg/m3), there was an increased cumulative risk of hospital admission for CKD in males of all ages, over time (Fig. 6) and overall (Table 2). As shown in Fig. 6c, the risk became apparent after 1,200 days of exposure in the 51- to 75-year age group. Exposure to medium or high concentrations of PM2.5 was found to increase the risk of CKD-related hospitalization by up to 2.5 times in males of all ages (Fig. 6 a-d). Among females, we observed no cumulative risk of hospitalization for CKD in those ≤ 18 years of age. However, in the 19- to 50-year and 51- to 75-year age groups, the cumulative risk appeared after a relatively short period of exposure (Fig. 6f–g and Table 2). As expected, exposure to PM2.5 presented a higher risk at 65 µg/m3 than at 15 µg/m3, for males and females alike. Notably, there is no more cumulative risk for women over 75 years of age (Fig. 6h and Table 2).

Fig. 6.

Fig. 6

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(a–d) Exposure–response curves showing the cumulative relative risk for hospitalization due to chronic kidney disease at different concentrations of fine particulate matter in various age groups of males. The gray shading represents the 95% confidence interval. (e–h) Exposure–response curves showing the cumulative relative risk for hospitalizations due to chronic kidney disease at different concentrations of concentrations of fine particulate matter in various age groups of females. The gray shading represents the 95% confidence interval.

Exposure–response curves of cumulative relative risk related to hospitalization for glomerular disease

As expected, exposure to PM2.5 presented a higher risk at 65 µg/m3 than at 15 µg/m3, as illustrated in Fig. 7 (a–d) and Table 3. The rate of hospital admissions for glomerular disease was higher in younger patients than in older patients, regardless of sex (Table 2). The cumulative risk of developing glomerular disease was found to be highest in young males exposed to PM2.5 at 65 µg/m3 for an extended period, in whom the risk was more than 5 times higher than was that for any other sex/age/exposure combination (Fig. 7a and Table 3).

Fig. 7.

Fig. 7

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Exposure–response curves showing the cumulative relative risk for hospitalization due to glomerular disease at different concentrations of fine particulate matter in various age groups of males (a and b) and females (c and d). The gray shading represents the 95% confidence interval.

Table 3.

Relative risk of hospitalization for glomerular disease over 2,000 days of exposure to 65 µg/m3 of fine particulate matter, by sex and age.

Age Hospitalization for GD
Males Females
(years) RR (95% CI) RR (95% CI)
0–40 1.067 (1.02–1.11) 1.02 (0.985–1.05)
 > 40 1.026 (1.006–1.05) 1.035 (0.962–1.10)
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GD, glomerular disease; RR, relative risk.

It has been hypothesized that air pollution is associated with an increased risk of membranous nephropathy. We analyzed the rates of hospital admission for membranous nephropathy and found that exposure to PM2.5 increased the cumulative risk of hospital admission for membranous nephropathy in males and females of all ages (Fig. 8). That risk was highest for men ≤ 40 years of age.

Fig. 8.

Fig. 8

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Cumulative relative risk (RR) for hospitalization due to membranous nephropathy for exposure to fine particulate matter (PM2.5) in various age groups of males and females.

Discussion

Our study provides comprehensive insights into the relationship between PM2.5 exposure and hospitalizations for kidney diseases in the city of São Paulo over 10 years. The results indicate a significant association between higher PM2.5 concentrations and increased risk of AKI, CKD, and glomerular diseases. Even exposure to PM2.5 at 15 µg/m3 can increase the risk of hospital admission. The WHO air quality guideline states that the annual average concentration of PM2.5 should not exceed 5 µg/m3, and that the 24-h average exposure should not exceed 15 µg/m3 on more than 3–4 days per year10.

We observed that PM2.5 exposure is associated with higher rates of hospitalization for kidney diseases, with varying risks across age groups and sexes. Specifically, younger populations (≤ 18 years of age) exhibited heightened sensitivity to the exposure, as evidenced by increased RR even at lower concentrations. In contrast, older adults (≥ 75 years of age), especially older men, showed a more pronounced risk with longer lag times. This suggests that younger individuals are more acutely affected by short-term exposures, whereas the elderly are more vulnerable to cumulative exposure over time. Younger and older individuals are both more sensitive to long-term PM2.5 exposure.

Exposure to air pollution is still estimated to cause millions of deaths and the loss of healthy years of life worldwide31–33. The burden of disease attributable to air pollution is now estimated to be on a par with other major global health risks such as tobacco smoking34. Air quality has markedly decreased in most low- and middle-income countries, mainly due to disorganized urbanization and an increase in the number of air pollution sources. The main source of air pollution in the city of São Paulo is the vehicle fleet5. Public transport is present but still inadequate for the size of the city. For instance, the current share of people per day using underground transportation in the greater metropolitan area of São Paulo is 4.2 million (19% of the total population of 22 million), compared with approximately 3.6 million (24% of the total population of 15 million) in the greater metropolitan area of London, England.

We found the risk of hospital admission for AKI to be higher in younger males (≤ 50 years of age) than in older males (> 50 years of age), probably because other conditions, such as sepsis, urinary tract obstruction, nephrotoxicity, and cardiovascular diseases, are more common in the former group35–37. It is important to point out that even at low levels of PM2.5 (15 µg/m3), there was an increased risk of hospitalization for AKI in males, although not in females. In low- and middle-income countries such as Brazil, AKI in females is strongly associated with preventable causes, including untreated urinary tract infections, puerperal sepsis, and preeclampsia38.

As expected, there was an increased risk of hospital admission for CKD at either PM2.5 concentration (15 or 65 µg/m3). Epidemiological studies have demonstrated that long-term exposure to PM2.5is associated with an increased risk of CKD3,11,12, CKD progression11, albuminuria13, and stage 5 CKD3.

A recent study, designated the CureGlomerulonephropathy study, enrolled prevalent patients with biopsy-confirmed minimal change disease, focal segmental glomerulosclerosis, membranous nephropathy, or immunoglobulin A nephropathy, within the first five years after diagnosis39. From both the CureGlomerulonephropathy and Nephrotic Syndrome Study Network cohorts, another study identified a subset of pediatric and adult patients who had at least two years of follow-up and validated census tract data available for air pollution exposure assessment15. To estimate ambient air quality, the authors of that study accessed a publicly available dataset providing estimated surface-level PM2.5 concentrations. They aimed to determine whether higher residential exposure to PM2.5 is associated with an increased risk of kidney disease progression and if air pollution exposure correlates with serum levels of proinflammatory biomarkers and activation of intrarenal inflammatory pathways. Baseline exposures to three pollutants (PM2.5, black carbon, and sulfate) were similar between the two cohorts and strongly correlated with each other. Patients exposed to pollutant levels above the median were more likely to be older, to be Black, and to have a lower baseline estimated glomerular filtration rate. During follow-up, 24% of the patients experienced disease progression, with some advancing to stage 5 CKD. In fully adjusted models controlling for age, baseline estimated glomerular filtration rate, race, and maternal level of education (as a proxy for socioeconomic status), exposure to PM2.5 and exposure to black carbon were both associated with an increased risk of disease progression.

Xu et al.40 studied the effect of air pollution on the changing pattern of glomerulopathy. They estimated the profile of and temporal change in glomerular diseases in an 11-year renal biopsy series, including 71,151 native biopsies. The authors found that each 10-µg/m3 increase in PM2.5 concentration was associated with a 14% higher risk of membranous nephropathy in regions with PM2.5 concentrations > 70 µg/m3. They also found that a higher 3-year average air quality index was associated with an increased risk of membranous nephropathy. It has yet to be elucidated why membranous nephropathy is associated with air pollution. Exposure to fine particulate promotes the production of autoantibodies and immunocomplexes41,42. One study showed that interleukin 4 content is elevated in the fetal portion of the placenta in rats exposed to air pollution43.

Some limitations of our study should be acknowledged. First, we relied on the ICD-10 codes recorded during patient hospitalizations, which could have resulted in missing data, given that not all relevant ICD-10 codes are always documented and some that are may be inaccurate. In addition, we used historical air pollution data from CETESB monitoring stations, which are often far apart and may not provide highly precise exposure estimates.

Conclusions

This study highlights the substantial influence of PM2.5 exposure on kidney health, demonstrating an association between long-term exposure to air pollution and increased risks of CKD, AKI, and glomerulopathy. The findings underscore the vulnerability of specific populations, particularly males and younger to middle-aged adults, to the deleterious effects of particulate matter. These results underscore the urgent need for public health policies aimed at reducing the levels of air pollution and mitigating its impact on kidney and overall health.

Supplementary Information

Supplementary Information. (288.5KB, pdf)

Author contributions

IDS and LA performed the data analysis; IDS, MEGC, ADP, IS, CFHW, JJTHR, SF, TRS, EDF, JK, AT, MFA and LA wrote the main manuscript text and IDS and TRS prepared Figs. 1, 2, 3, 4, 5, 6, 7, 8. All authors reviewed the manuscript.

Funding

This work was supported by a joint consortium grant on healthy aging (www.pmkidney.com) from the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO, Dutch Research Council) and the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, São Paulo Research Foundation; Grant nos. 2019/19433–0 and 2016/18438–0). IS, EDF, LA, and MFA are the recipients of grants from the Brazilian Conselho Nacional de Desenvolvimento Científico e Tecnológico (National Council for Scientific and Technological Development; Grant nos. 140512/2021–7, 313210/2022–5, 309683/2021–1, and 306849/2007–0, respectively). CFHW is financially supported by the São Paulo Research Foundation (FAPESP), Brasil (Grants #2020/07674–0 and #2022/13888–9).AT is financially supported by the NWO–FAPESP joint grant on healthy aging, executed by the ZorgOnderzoek Nederland/Medische Wetenschappen (ZonMw, Netherlands Healthcare Research/Medical Sciences; Grant no. 457002002) and Junior Kolff grant from the Dutch kidney Foundation.

Data availability

The datasets analyzed in this study are available online: https://github.com/iaradasilva/supplementary-data/tree/main).

Declarations

Competing interests

The authors declare no competing interests.

Footnotes

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary Information. (288.5KB, pdf)

Data Availability Statement

The datasets analyzed in this study are available online: https://github.com/iaradasilva/supplementary-data/tree/main).

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