Epidemiological Transition of Renal Mortality in Chiapas (2000–2024): Autonomy of CKDu and the Rise of Hypertensive Nephropathy—A Time‐Series Ecological Study

ABSTRACT

Aim

Chronic kidney disease of non‐traditional aetiology (CKDu) has been described in agricultural regions worldwide, yet its contribution to renal mortality in Mexico remains poorly characterised. This study aimed to characterise renal mortality trends in Chiapas and evaluate the autonomy of CKDu relative to metabolic causes.

Method(s)

An ecological time‐series study used DGIS mortality microdata for Chiapas, 2000–2024. Renal deaths (n = 46 301) were classified by ICD‐10 into DKD, HN, CKDu, ReNe and OthR. Age strata were 0–14, 15–29, 30–44, 45–59 and ≥ 60 years. Age‐standardised mortality rates were calculated, APC estimated using log‐linear regression, and sociodemographic contrasts assessed using binomial logistic regression (CKDu vs. DKD). Temporal independence between CKDu and diabetes trends was evaluated using trend‐correlation and a binomial test for diagnostic substitution.

Results

Among individuals aged 15–44 years, CKDu was the leading renal cause of death (44.2%), compared with 27.5% for DKD. CKDu comprised 32.9% of renal deaths in men versus 26.2% in women. The highest mortality growth occurred in men aged 30–44 years (APC 4.01%; p < 0.001). Among agricultural‐sector decedents, mortality was more likely to be attributed to CKDu than DKD (OR 1.61). HN showed the fastest overall growth (APC 6.72%). Trend‐correlation indicated that 64.5% of CKDu temporal variance was independent of diabetes trends (R ² = 0.3547), with no evidence of diagnostic substitution (p = 0.7).

Conclusion

Renal mortality in Chiapas shows a dual burden in which CKDu exhibits autonomy, consistent with chronic interstitial nephritis in agricultural communities, and supports surveillance and prevention addressing occupational and environmental determinants.

Summary at a Glance

Renal mortality in Chiapas shows a dual burden characterised by persistent chronic kidney disease of non‐traditional aetiology (CKDu) alongside expanding metabolic and vascular causes. CKDu disproportionately affects working‐age populations and exhibits epidemiological autonomy from diabetes‐related renal mortality. Hypertensive nephropathy is the fastest‐growing cause, underscoring environmental vulnerability and cardiovascular risk.

Renal mortality in Chiapas reflects a dual burden in which CKDu persists as a predominant cause among young agricultural workers, while hypertensive nephropathy shows the fastest growth, driven by expanding metabolic and vascular risks. CKDu demonstrates temporal autonomy from diabetes, indicating distinct socio‐environmental determinants. These patterns highlight the need for targeted surveillance and prevention strategies in vulnerable rural populations.

1. Introduction

Chronic kidney disease (CKD), commonly defined as a sustained reduction in glomerular filtration rate for at least 3 months [1], has become a major cause of mortality in Mexico and represents an increasing public health concern largely associated with Type 2 diabetes mellitus (T2DM) and arterial hypertension (HTN) [2]. In addition to these metabolic conditions, a non‐traditional form—chronic kidney disease of unknown or non‐traditional aetiology (CKDu)—has been reported in agricultural settings. CKDu is characterised by tubulointerstitial injury in individuals without metabolic risk factors and disproportionately affects young manual labourers [3].

Similar patterns have been described in Sri Lanka, India and Central America, where environmental exposures and physically demanding work have been linked to renal injury. In Mexico, the state of Chiapas presents comparable structural conditions, including tropical climate, agricultural intensification and marked socioeconomic vulnerability.

Chiapas, situated in south‐eastern Mexico and bordering Guatemala, shares environmental and productive features with neighbouring Central American regions. Its predominantly rural population, substantial proportion of Indigenous inhabitants and the lowest level of human development in the country contribute to persistent structural disadvantage. Limited access to healthcare further reinforces this vulnerability.

These conditions form a risk environment characterised by heat stress, agrochemical exposure and precarious labour. Within this context, the Soconusco region—located along the coastal strip adjacent to Guatemala—has drawn attention due to documented CKD incidence [4], although long‐term mortality patterns in Chiapas remain insufficiently described. It is not yet clear whether renal mortality is shifting towards younger age groups or whether CKDu displays temporal and demographic features distinct from metabolic causes.

Given the parallels with the Central American epidemic and the relevance for public health planning, examining renal mortality trends in Chiapas is warranted. This study characterises renal mortality from 2000 to 2024, assesses age‐related changes in disease burden and evaluates the epidemiological distinctiveness of CKDu relative to metabolic causes. We hypothesised that CKDu mortality in Chiapas follows a temporal and demographic pattern partly independent of diabetes‐related renal mortality, consistent with an epidemiologically autonomous profile.

2. Methods

2.1. Study Design and Data Sources

An ecological time‐series study was carried out using individual mortality microdata from the General Directorate of Health Information (DGIS) of the Mexican Ministry of Health [5]. Records for the state of Chiapas were examined across a 25‐year period, from 1 January 2000 to 31 December 2024. All deaths with a renal condition listed as the underlying cause were retained. Records lacking defined information on age or sex were removed to maintain analytical consistency.

As an ecological analysis based on routinely collected mortality data, the study was intended to describe population‐level patterns and temporal associations; individual‐level causal inference was not feasible.

2.2. Classification of Renal Causes of Death

Underlying causes of death were coded according to the International Classification of Diseases, Tenth Revision (ICD‐10) [6]. Diabetic kidney disease (DKD) was identified using codes E10.2, E11.2, E12.2, E13.2 and E14.2, while hypertensive nephropathy (HN) corresponded to code I12.

Chronic kidney disease of non‐traditional causes (CKDu) was defined operationally using CKD codes N18.0, N18.2, N18.3, N18.4, N18.5, N18.8, N18.9 and N19, in the absence of diabetes‐related or hypertensive renal codes, following international surveillance recommendations for CKDu [7]. This category therefore represents a non‐metabolic, non‐vascular CKD proxy within mortality records. Any residual misclassification would be expected to be non‐differential with respect to sociodemographic variables and to bias associations towards the null.

Renal neoplasms and malformations (ReNe) comprised codes C64, C79.0, Q61 and Q63. A further category of other renal diagnoses (OthR) encompassed renal and urinary system conditions not included in the preceding groups, defined by codes N00.8, N00.9, N01.9, N02.2, N02.8, N03.2, N03.9, N04.5, N04.8, N04.9, N05.1, N05.2, N05.8, N05.9, N06.9, N10, N11.0, N11.1, N11.9, N12, N13.2, N13.3, N13.5, N13.6, N13.9, N14.0, N15.1, N15.9, N17.0, N17.8, N17.9, N20.0, N20.2, N23, N25.8, N26, N27.0, N27.1, N28.0, N28.1, N28.8 and N28.9.

2.3. Sociodemographic Profile Analysis

To describe population groups most affected by renal mortality, a descriptive sociodemographic analysis was undertaken. An analytical dataset was assembled from individual DGIS mortality records, allowing examination of deaths by sex, predefined age groups and selected social variables, particularly occupation and educational level, as recorded on death certificates. These variables were interpreted as contextual and structural markers of vulnerability rather than direct measures of individual exposure.

Crude mortality rates were calculated, and absolute frequencies and proportional distributions were reviewed to outline the baseline sociodemographic structure of renal mortality across strata, forming the basis for subsequent temporal and multivariable analyses.

2.4. Population Stratification and Age Standardisation

Mortality records were stratified by sex and four predefined age groups (15–29, 30–44, 45–59 and ≥ 60 years). Mortality rates were computed per 100 000 inhabitants using mid‐year population projections from the National Population Council (CONAPO) for 2000–2024 [8]. To reduce bias related to population ageing and demographic shifts over time, all rates were age‐standardised using the direct method [9], employing the WHO World Standard Population, as distributed by the SEER programme, as the reference [10].

2.5. Temporal Distribution and Contingency Analysis

To assess changes in the aetiological structure of renal mortality over time, deaths were grouped into 5‐year periods. For each quinquennium, absolute and relative frequencies by aetiology were calculated. Associations between aetiology and time period were evaluated using contingency table analysis, with overall significance assessed through Pearson's chi‐squared tests. Pearson residuals were examined to identify deviations from expected frequencies, and Monte Carlo simulations with 10 000 iterations were applied when sparse cell counts were present.

2.6. Trend and Growth‐Velocity Analysis

Temporal changes in renal mortality were examined by estimating the annual percentage change (APC) using log‐linear regression models [11]. Models were fitted with the natural logarithm of the age‐standardised mortality rate as the dependent variable and calendar year as the independent variable, assuming a constant rate of change over time. APC estimates were calculated by sex and age group and by aetiology, enabling comparison of growth velocities between CKDu and traditional metabolic and vascular causes. Statistical significance was assessed using 95% confidence intervals, and all tests were two‐sided.

2.7. Risk Factors and Rate Ratios

Associations between selected sociodemographic characteristics and cause of death were examined using binomial logistic regression models, contrasting CKDu versus DKD as the outcome. Results are presented as odds ratios (OR) with corresponding 95% confidence intervals (95% CI). These models were intended to describe differential mortality patterns rather than estimate causal risk.

Rate ratios (RR) were also calculated using CKDu as the reference category to assess temporal changes in the relative magnitude of renal mortality by aetiology.

2.8. Validation of Aetiological Autonomy

The epidemiological independence of CKDu from metabolic causes was evaluated through correlation analysis of temporal trends, complemented by a binomial test to assess the possibility of diagnostic substitution. The stability of diagnostic categories was reviewed across the study period to identify sustained substitution patterns or systematic reclassification.

2.9. Statistical Software

All data processing and statistical analyses were conducted using R software (version 4.3.2) [12]. Data management, aggregation and stratification were performed using dplyr and tidyr, while database organisation and validation were supported by the openxlsx package [13].

3. Results

3.1. Temporal Dynamics of Mortality Causes

Changes in the distribution of causes of death over the past 25 years were examined. The evolution of renal health in Chiapas reflects a gradual reconfiguration of traditional and emerging pathologies. As shown in Table 1, CKDu maintained a stable presence throughout the early period (2000–2004), whereas DKD and HN increased progressively. By 2015–2019, DKD attained its highest relative contribution, whilst HN displayed the most pronounced rise in 2020–2024. This coexistence indicates that Chiapas faces a dual burden of disease: a persistent non‐traditional foundation alongside a marked expansion of modern metabolic causes.

TABLE 1.

Contingency analysis and Pearson residuals ^a for the aetiology of renal mortality by 5‐year periods in Chiapas, 2000–2024.

Aetiology	2000–2004 (n/R p) b	2005–2009 (n/R p) b	2010–2014 (n/R p) b	2015–2019 (n/R p) b	2020–2024 (n/R p) b
CKDu	1733/12.72	2143/3.49	2576/−1.86	3261/−5.49	3905/−2.90
DKD	1697 / −8.54	3230/−0.26	4498/2.05	6340/6.26	6469/−2.57
HN	200 / −8.97	436/−6.00	726/−1.95	1090/1.28	1526/9.58
ReNe	175/2.40	212/−1.00	287/−1.05	407/−0.16	475/0.35
OthR	541/3.71	736/0.70	998/1.08	1107/−5.24	1533/1.47
Total	4346	6757	9085	12 205	13 908

Abbreviations: CKDu, chronic kidney disease of non‐traditional aetiology; df, degrees of freedom; DKD, diabetic kidney disease; HN, hypertensive nephropathy; OthR, other renal diagnoses; ReNe, renal neoplasms and malformations; R _p, Pearson residual.

^a Global association was evaluated using Pearson's chi‐squared test (χ ² = 605.54, df = 16, p < 0.0001).

^b R _p denotes Pearson residuals; absolute values > 2 (shown in bold) indicate significant local deviations from expected frequencies under independence.

3.2. Sociodemographic Profile

The sociodemographic profile of renal mortality (Table 2) encompasses 46 301 deaths in Chiapas from 2000 to 2024. DKD was more frequent among women, whereas CKDu accounted for a larger proportion among men. The age distribution reveals a shift towards earlier mortality: in the 15–44‐year group, CKDu was the predominant renal cause, representing 44.2% of deaths compared with 27.5% attributed to DKD. Social gradients were evident: 27.4% of CKDu decedents worked in agriculture, and 41.6% lacked formal schooling, reflecting a socially patterned, non‐metabolic mortality profile. These contrasts provide a contextual baseline for interpreting temporal redistribution across the study period.

TABLE 2.

Sociodemographic profile of renal mortality and associated risk factors (CKDu vs. DKD) in Chiapas, Mexico, 2000–2024 (N = 46 301).

Variable/category	CKDu (n)	DKD (n)	HN (n)	ReNe (n)	OthR (n)	Total (n)	OR (95% CI) a
Total cases	13 618	22 234	3978	1556	4915	46 301	—
Sex
Male	8852	12 105	2068	887	3024	26 936	1.38 (1.29–1.47)*
Female	4766	10 129	1910	669	1891	19 365	1.00 (Ref)
Age group b
0–14 years	455	42	24	398	536	1455	—
15–29 years	1722	785	142	156	552	3357	2.51 (2.35–2.67) c , *
30–44 years	4210	8245	856	382	1124	14 817	—
45–59 years	4952	10 542	1724	458	1288	18 964	1.00 (Ref) c
≥ 60 years	2279	2620	1232	162	1415	7708	—
Agricultural sector
Yes	6245	7122	1182	452	1392	16 393	1.61 (1.50–1.74)*
No/others	7373	15 112	2796	1104	3523	29 908	1.00 (Ref)
Education level
No schooling	4820	7025	1482	352	1324	15 003	1.61 (1.45–1.78)*
Primary	6124	10 852	1652	622	2015	21 265	0.99 (0.90–1.10)
Secondary	1452	2425	452	315	812	5456	1.00 (Ref)
High school	1222	1932	392	267	764	4577	1.11 (0.98–1.25)

Abbreviations: CI, confidence interval; CKDu, chronic kidney disease of non‐traditional causes; DKD, diabetic kidney disease; HN, hypertensive nephropathy; OR, odds ratio; OthR, other renal diagnoses; Ref, reference category; ReNe, renal neoplasms and malformations.

^a Dependent variable in the binomial logistic regression model: cause of death (1 = CKDu; 0 = DKD). OR represents the relative odds of death being attributed to CKDu compared with DKD.

^b Decedents in the 0–14 years stratum were included exclusively for the completeness of the descriptive profile of the population and were excluded from the log‐linear regression and logistic models. All occupational classifications were standardised using the CMO and SINCO national catalogues.

^c For the age variable, the multivariate model was fitted using only the four adult age categories shown in the table (15–29, 30–44, 45–59 and ≥ 60). Secondary education level and non‐agricultural occupation served as reference categories.

^* p < 0.001.

3.3. Risk Factors and OR

After establishing temporal dynamics, regression models (Table 3) indicate that the CKDu mortality profile in Chiapas is characterised by working‐age agricultural workers. Age emerges as the most influential biological factor: individuals aged 20–49 years have higher odds of CKDu compared with DKD than older adults, representing a departure from patterns observed in traditional metabolic diseases. Men exhibit 38% higher odds than women, consistent with labour conditions and occupational exposure in the agricultural sector. Socioeconomic vulnerability and work‐related stressors therefore shape the region's epidemiological profile.

TABLE 3.

Evolution of age‐standardised renal mortality rates, annual percentage change (APC) and rate ratios (RR) by aetiology.

Renal aetiology	2000 rate (95% CI) a	2024 rate (95% CI) a	APC (%) (95% CI) b	RR 2000 c	RR 2012 c	RR 2024 c
CKDu	9.20 (8.15–10.25)	11.20 (10.43–11.97)	0.81 (0.36–1.26)*	1.00 (Ref)	1.00 (Ref)	1.00 (Ref)
DKD	10.58 (9.48–11.68)	16.63 (15.76–17.50)	3.09 (1.97–4.23)**	1.15	1.71	1.49
HN	0.92 (0.59–1.25)	4.42 (3.97–4.87)	6.72 (5.84–7.61)**	0.1	0.26	0.4
ReNe	0.71 [NC]	1.33 [NC]	2.10 (1.33–2.86)**	—	—	—
OthR	2.68 [NC]	4.66 [NC]	1.84 (1.28–2.40)**	—	—	—

Note: [NC] not calculated: The 95% confidence intervals for the point rates of ReNe and OthR were not estimated in the primary data cubes because these categories act as structural descriptive reference groups for global renal mortality; the longitudinal rate ratio (RR) modelling was explicitly restricted to tracking the metabolic transition (DKD, HN) against the non‐traditional variant (CKDu).

Abbreviations: CI, confidence interval; CKDu, chronic kidney disease of non‐traditional aetiology; DKD, diabetic kidney disease; HN, hypertensive nephropathy; OthR, other renal diagnoses; Ref, reference category; ReNe, renal neoplasms and malformations; RR, rate ratio.

^a Age‐standardised mortality rates per 100 000 inhabitants, calculated via the direct method using the WHO World Standard Population as distributed by the SEER programme.

^b The APC reflects the average yearly rate of increase or decrease estimated via log‐linear regression models assuming a constant rate of change (2000–2024).

^c Rate ratios (RR) measure the longitudinal change in relative risk taking the CKDu category as the constant baseline reference (RR = 1.00).

^* p < 0.01.

^** p < 0.001.

3.4. Sex‐Stratified APC Trends

The sex‐stratified analysis of APC trends (Figure 1) reveals marked epidemiological dimorphism, with a progressive shift in renal mortality towards younger ages that disproportionately affects males. Men aged 30–44 years showed the fastest historical growth (APC: 4.01%; p < 0.001), doubling the rate observed in women of the same age range. The divergence is more pronounced in the 15–29‐year group, where men displayed a strong upward trend (3.32%). Together, these patterns suggest that sex acted as a demographic marker associated with differential mortality patterns, whilst metabolic causes dominate at older ages and premature mortality appears driven by determinants that selectively affect the male workforce, consistent with heat stress and occupational exposure.

FIGURE 1.

Trends in age‐standardised renal mortality rates by specific aetiology in Chiapas, Mexico, 2000–2024. Comparative distribution of overall renal mortality between men and women across specific age strata. Values above the bars indicate the Annual Percentage Change (APC) calculated via log‐linear regression over the 25‐year period. Asterisks denote statistical significance (*** p < 0.001). Rates are age‐standardised via the direct method per 100 000 inhabitants using the WHO World Standard Population as the reference database.

3.5. APC and Rate Ratio Trends

The APC and rate ratio (RR) analysis (Table 3, Figure 1) enables comparison of growth velocity whilst minimising bias related to population ageing. Results confirm an upward trend across all aetiologies, though at different rates. HN exhibited the fastest expansion (APC: 6.72%), followed by DKD (APC: 3.09%), while CKDu showed a slow, stable trajectory (APC: 0.81%), consistent with its structural nature. Longitudinal rate ratios confirm this metabolic shift: the DKD‐to‐CKDu gap peaked in 2012 (RR: 1.71) before settling at 1.49 in 2024, while the relative risk of HN increased fourfold, from 0.10 in 2000 to 0.40 in 2024. Given the magnitude of these trends, a final step was required to verify that observed patterns were not artefacts of diagnostic substitution or reporting bias.

3.6. Validation and Aetiological Autonomy

To ensure data integrity and exclude registration bias, potential misclassification or coding errors between DKD and CKDu were assessed through a two‐phase validation protocol. First, a trend‐correlation analysis for 2000–2024 produced a coefficient of determination (R ² = 0.3547), indicating that the temporal trajectory of diabetes mortality accounts for only 35.5% of CKDu variability. The remaining 64.5% of independent variance suggests that, although both conditions coexist within the regional profile, they are shaped by distinct biological determinants and socio‐environmental factors. This substantial residual variance challenges the interpretation of CKDu as a reporting artefact of the diabetes epidemic.

Second, a diagnostic‐substitution phenomenon was excluded using a binomial test (p = 0.7). This finding demonstrates that the increase in CKDu is not a statistical artefact resulting from clinicians shifting away from diabetes diagnoses, but represents an autonomous epidemiological phenomenon. Persistence analysis indicated that the maximum period of diagnostic opposition lasted only 2 years, with no evidence of sustained substitution patterns across the 25‐year period.

The data demonstrate dynamic behaviour: the RR was 1.15 in 2000, peaked at 1.71 in 2012, and declined to 1.49 by 2024. This fluctuation confirms that each disease follows a distinct trajectory. Whilst diabetes aligns with the metabolic transition, CKDu follows an independent course shaped by population dynamics and occupational exposures. These findings reinforce the reliability of DGIS records and support the biological autonomy of the non‐traditional category.

4. Discussion

4.1. Epidemiological Framework

The characterisation of CKD in Chiapas reveals a complex public health landscape in which traditional metabolic causes coexist with emerging non‐traditional aetiologies. Although the progression of diabetes‐ and hypertension‐related renal pathology mirrors national patterns [14], the regional profile diverges in ways that underscore the influence of socio‐environmental determinants. The concentration of renal mortality in marginalised territories, coupled with the predominance of non‐traditional causes among younger adults, situates Chiapas within a broader Central American context where structural precariousness, labour intensity and environmental exposure converge to shape renal vulnerability. This alignment with neighbouring agricultural communities suggests that CKD in Chiapas cannot be understood solely through metabolic transitions, but rather through a multifactorial framework in which social exclusion and environmental stressors play central roles.

4.2. Person Dimension: Vulnerability Profile

The demographic and occupational profile of affected individuals in Chiapas diverges markedly from patterns typically associated with age‐related renal decline. Mortality records identify a predominantly male population concentrated in early and mid‐working life, engaged primarily in agricultural labour, consistent with chronic interstitial nephritis in agricultural communities (CINAC). According to Vervaet et al. [3] and Orantes et al. [15], CINAC represents a tubulointerstitial nephropathy driven not by metabolic risk factors but by sustained exposure to environmental determinants, including heat stress, dehydration and agrochemical contact.

Rivera‐Chavarría et al. [16] report that mortality from non‐traditional causes predominates among groups experiencing precarious labour conditions, reinforcing the notion of a disease rooted in social exclusion. This pattern of premature mortality during economically productive years echoes findings from other regions of Mexico, where persistent renal damage has been documented in adolescents from communities with a high prevalence of kidney disease of unknown origin [17]. Such evidence suggests that renal injury may begin early in life, progressing silently until manifesting as excess mortality during adulthood.

Cerón [18] emphasises that in Guatemala, social determination is inseparable from economic precariousness—conditions similarly reproduced in south‐eastern Mexico. The application of standardised definitions [7] confirms that the clinical profile observed in Chiapas aligns with that of the Central American isthmus, indicating exposure to comparable nephrotoxic pressures, particularly heat stress and agrochemical exposure. Together, these findings highlight a vulnerability profile shaped by structural disadvantage, environmental strain and occupational intensity.

4.3. Place Dimension: Geography of Environmental Risk

The spatial distribution of CKD in Chiapas reveals distinct territorial patterns that reflect the interplay between productive landscapes, climatic conditions and social marginalisation. Sugarcane production is concentrated in the Plains (Los Llanos) and the Soconusco region. Rivero‐Pérez et al. [4] identified Soconusco—located along the coastal strip bordering Guatemala—as a critical territory where CKD incidence clusters in areas characterised by intensive agriculture and extreme temperatures. Arce‐Moguel [19] argues that sugarcane cultivation functions as a primary risk determinant owing to the socio‐environmental vulnerability it generates, including heat stress, precarious labour conditions and limited access to preventive healthcare. This dynamic aligns with evidence from Hansson et al. [20] in Central America, where municipalities with high sugarcane cultivation intensity and extreme heat exhibit the highest mortality rates from non‐traditional nephropathies.

These spatial patterns suggest that CKDu risk is not randomly distributed but organised along productive and climatic landscapes where environmental exposure, labour intensity and social marginalisation converge. Recognising environmental vulnerability requires acknowledging that nephrotoxic pressure in agricultural communities is multifactorial and extends beyond agrochemical use. Chronic exposure to heavy metals and metalloids—particularly arsenic, cadmium and lead—constitutes a well‐characterised pathway in chronic tubulointerstitial injury, as these elements act as direct tubular toxins [3, 21]. In marginalised settings, contamination of water sources and soils—whether due to intrinsic geochemical conditions or impurities in phosphate fertilisers—may interact synergistically with heat stress and recurrent dehydration among agricultural workers.

This multicausal model mirrors CKDu crises in South Asia, including Sri Lanka and Uddanam, where co‐exposure to heavy metals in drinking water and organophosphate pesticides drives premature renal damage. Within the Mexican context, this pathway aligns with configurations documented in other focal areas of idiopathic renal disease: in Jalisco, García‐García et al. [22] emphasise the role of structural poverty; in Veracruz, Valdivia‐Rivera et al. [23] identify water contamination as a key environmental determinant; and in Aguascalientes, exposure to environmental toxins has similarly been implicated [21]. Persistently elevated renal mortality in Chiapas underscores the need for systematic environmental monitoring frameworks capable of quantifying these metallic compounds in vulnerable populations.

Marginalisation further amplifies nephrotoxic exposures through limited access to sanitation, safe water and environmental protections, particularly in rural agricultural zones. The persistence of elevated renal mortality in these territories underscores that environmental determinants, interacting with social and occupational vulnerability, play a central role in shaping the regional burden of kidney disease, beyond metabolic risk pathways alone.

4.4. Time Dimension: Temporal Dynamics and CKDu Autonomy

Analysis of the historical series (2000–2024) provides strong evidence for aetiological independence: 64.5% of the variance in mortality from non‐traditional causes is statistically independent of diabetes trends. This lack of temporal synchrony challenges the interpretation that CKDu is a by‐product of record‐keeping limitations; if it were merely a reporting artefact of diabetes, both trajectories would be expected to exhibit a close and sustained correlation over time.

The evolution of the relative risk presented in Table 3 further reinforces this autonomy. The risk gap was dynamic, beginning with an RR of 1.15 in 2000, rising to 1.71 in 2012 and declining to 1.49 by 2024. This fluctuating pattern is compatible with time‐varying environmental or occupational exposures, in contrast to the more gradual and predictable progression of diabetes. Together, these temporal dynamics support the epidemiological autonomy of CKDu in Chiapas.

4.5. Emergence of HN

Whilst the autonomy of CKDu represents the most distinctive epidemiological challenge in south‐eastern Mexico, the data reveal a parallel and concerning rise in HN, with an APC of 6.72%, positioning it as the fastest‐growing cause of renal mortality in the state in relative terms. This phenomenon is not isolated; it forms part of a broader global trend in which, as noted by Jager et al. [24], kidney disease is increasingly shaped by vascular and metabolic transitions, and mechanistic pathways in HN have been highlighted [25]. In the context of Chiapas, the increase in deaths attributed to hypertension as a primary cause suggests a convergence between regional environmental vulnerability and the expansion of traditional cardiovascular risk factors.

From a pathophysiological perspective, this rise in HN warrants careful interpretation. It is plausible that a proportion of these deaths represent cases of secondary hypertension arising from early‐stage, undiagnosed CKDu. In settings of heat stress and recurrent dehydration—characteristic of agricultural zones in Chiapas—volume depletion may chronically activate the renin–angiotensin–aldosterone system (RAAS). This state of compensatory hyperfiltration and tubulointerstitial inflammation can manifest clinically as arterial hypertension before substantial declines in glomerular filtration rate are evident. In such contexts, hypertension may function as a clinical sentinel of an underlying environmental insult that, if not recognised promptly as CKDu, is ultimately classified under HN [1, 26].

The potential severity of this trend lies in its capacity to overwhelm primary care services. Weisman et al. [1] highlight that most CKD patients are initially managed in general practice, where blood‐pressure control represents the cornerstone of efforts to delay renal fibrosis. However, in highly marginalised regions, late detection of systemic arterial hypertension accelerates irreversible structural damage. In Mexico, Reyna‐Sevilla et al. [27] documented a 45.8% increase in demand for renal consultations, identifying hypertension and diabetes as the principal drivers. For Chiapas, the convergence of a non‐traditional epidemic (CINAC) with the continued advance of vascular nephropathy creates conditions that threaten to overwhelm the state healthcare system.

Comparable system‐level pressures have been reported in South Asia, particularly in Sri Lanka and eastern India, where CKDu has emerged among agricultural populations exposed to heat stress, physically demanding labour and chronic environmental exposures [28, 29]. In Sri Lanka, CKDu has been extensively documented as a tubulointerstitial nephropathy affecting rural farmers without classical metabolic risk factors, characterised by late clinical presentation and substantial strain on primary healthcare services [28]. Similarly, in the Uddanam region of Andhra Pradesh, India, endemic nephropathy has been described among young agricultural workers, often detected at advanced stages and associated with limited diagnostic capacity in rural settings [29]. Although environmental contexts differ, these regions share a convergent pattern of occupational stress, environmental exposure and constrained health‐system capacity.

The parallels with Chiapas indicate that the observed convergence of non‐traditional renal disease and HN is not a local anomaly, but a recurring global challenge for health systems serving agricultural communities.

4.6. Study Limitations and Scope

The findings should be interpreted in light of the constraints inherent to the ecological design and the potential for ecological fallacy. As the analysis relies on aggregated mortality data from the DGIS, it is not possible to establish direct individual‐level causality between occupation and death. Furthermore, the model does not capture individual exposure variables such as precise heat stress, hydration practices or specific agrochemical contact. Nevertheless, the robustness of a 25‐year historical series and the use of standardised microdata provide strong population‐level validity for identifying long‐term trends and quantifying the magnitude of the renal health emergency in Chiapas.

5. Conclusions

The epidemiological evidence demonstrates that Chiapas constitutes a focal territory within a renal crisis of mixed aetiology, where social vulnerability consistently emerges as the principal underlying determinant. The finding that 64.5% of the variance in mortality from non‐traditional causes is independent of diabetes mellitus indicates that a substantial proportion of cases align with the CINAC phenomenon. This diagnostic autonomy—reinforced by the dynamic behaviour of the relative risk, which peaked at 1.71—suggests exposure to environmental and occupational pressures that are not adequately captured by conventional clinical frameworks for chronic degenerative diseases.

Chiapas reflects the broader Central American epidemic, characterised by a risk landscape shaped by social exclusion, heat stress and environmental vulnerability. The marked shift of renal mortality towards younger age groups reveals a pattern of premature death that exposes a critical period of vulnerability during the peak productive years of the male workforce. This profile is consistent with patterns documented in other CKDu‐affected regions, including South Asia, where combinations of occupational strain, environmental stress and delayed diagnosis have influenced renal outcomes in agricultural communities.

Addressing the renal health emergency in Chiapas requires moving beyond reliance on secondary mortality data and advancing towards primary source research. Cohort studies in agricultural communities are essential to evaluate nephrotoxic exposure and early tubular damage biomarkers directly. These efforts should be complemented by implementing sentinel epidemiological surveillance systems using internationally standardised case definitions to distinguish CKDu from diabetic and HN at the primary care level [7]. In parallel, establishing environmental and occupational monitoring programmes to regulate hydration and rest conditions in field labour, alongside strict water‐quality surveillance in regions with intensive agrochemical use [3, 20], remains a priority. Strengthening vascular‐damage prevention through improved blood‐pressure monitoring in rural clinics is also critical to avert premature progression to renal replacement therapies.

Ultimately, mortality data capture only one dimension of a broader problem rooted in rural precariousness. Protecting renal health in south‐eastern Mexico requires translating epidemiological evidence into social and environmental policies capable of reducing exposure, strengthening primary care capacity and safeguarding the health of agricultural communities.

Author Contributions

Francisco Emmanuel Arce Moguel: conceptualisation, methodology, data curation, formal analysis, writing – original draft, writing – review and editing. Benito Salvatierra Izaba: methodology, formal analysis, validation, writing – review and editing.

Funding

The authors have nothing to report.

Ethics Statement

The authors have nothing to report.

Conflicts of Interest

The authors declare no conflicts of interest.

Data Availability Statement

The data that support the findings of this study are publicly available from the General Directorate of Health Information (DGIS) at http://www.dgis.salud.gob.mx/.