Evidence map›Paper›PMID 39099652›Full record

ArticlePeerJ2024

Prevalence and metabolic risk factors of chronic kidney disease among a Mexican adult population: a cross-sectional study in primary healthcare medical units.

Alfonso R Alvarez Paredes, Anel Gómez García, Martha Angélica Alvarez Paredes, Nely Velázquez, Diana Cindy Ojeda Bolaños, Miriam Sarai Padilla Sandoval, Juan M Gallardo, Gerardo Muñoz Cortés, Seydhel Cristina Reyes Granados, Mario Felipe Rodríguez Morán and 3 more

Abstract read
In one paragraph

Article in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Alfonso R Alvarez ParedesFacultad de Ciencias Médicas y Biológicas "Dr. Ignacio Chávez", Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán, Mexico.
Anel Gómez GarcíaCentro de Investigación Biomédica de Michoacán, Instituto Mexicano del Seguro Social, Morelia, Michoacán, Mexico.
Martha Angélica Alvarez ParedesUnidad Médica de Atención Ambulatoria/Unidad de Medicina Familiar Núm. 75, Instituto Mexicano del Seguro Social, Morelia, Michoacán, Mexico.
Nely VelázquezUnidad de Medicina Familiar Núm. 80, Instituto Mexicano del Seguo Social, Morelia, Michoacán, Mexico.
Diana Cindy Ojeda BolañosUnidad de Medicina Familiar Núm. 84, Instituto Mexicano del Seguro Social, Morelia, Michoacán, Mexico.
Miriam Sarai Padilla SandovalUnidad de Medicina Familiar Núm. 82, Instituto Mexicano del Seguro Social, Zamora, Michoacán, Mexico.
Juan M GallardoUnidad de Investigación Médica en Enfermedades Nefrológicas, Hospital de Especialidades, Centro Médico Nacional Siglo XXI, Instituto Mexicano del Seguro Social, Mexico City, Mexico.
Gerardo Muñoz CortésCoordinación Auxiliar Médica de Investigación en Salud, Órgano de Operación Administrativa Desconcentrada, Instituto Mexicano del Seguro Social, Morelia, Michoacán, Mexico.
Seydhel Cristina Reyes GranadosCentro de investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, A.C., Consejo Nacional de Humanidades, Ciencia y Tecnología, Guadalajara, Jalisco, Mexico.
Mario Felipe Rodríguez MoránCentro de investigación y Asistencia en Tecnología y Diseño del Estado de Jalisco, A.C., Consejo Nacional de Humanidades, Ciencia y Tecnología, Guadalajara, Jalisco, Mexico.
Joaquin TrippAmphora Health, Morelia, Michoacán, Mexico.
Arturo Lopez PinedaAmphora Health, Morelia, Michoacán, Mexico.
Cleto Alvarez AguilarFacultad de Ciencias Médicas y Biológicas "Dr. Ignacio Chávez", Universidad Michoacana de San Nicolás de Hidalgo, Morelia, Michoacán, Mexico.

Funding

Coordination of Health Research FIS/IMSS/PROT/G17-2/1719 of the Instituto Mexicano Seguro Social
6 · The paper itself

Abstract

Introduction: The intricate relationship between obesity and chronic kidney disease (CKD) progression underscores a significant public health challenge. Obesity is strongly linked to the onset of several health conditions, including arterial hypertension (AHTN), metabolic syndrome, diabetes, dyslipidemia, and hyperuricemia. Understanding the connection between CKD and obesity is crucial for addressing their complex interplay in public health strategies. Objective: This research aimed to determine the prevalence of CKD in a population with high obesity rates and evaluate the associated metabolic risk factors. Material and Methods: In this cross-sectional study conducted from January 2017 to December 2019 we included 3,901 participants of both sexes aged ≥20 years who were selected from primary healthcare medical units of the Mexican Social Security Institute (IMSS) in Michoacan, Mexico. We measured the participants' weight, height, systolic and diastolic blood pressure, glucose, creatinine, total cholesterol, triglycerides, HDL-c, LDL-c, and uric acid. We estimated the glomerular filtration rate using the Collaborative Chronic Kidney Disease Epidemiology (CKD-EPI) equation. Results: Among the population studied, 50.6% were women and 49.4% were men, with a mean age of 49 years (range: 23-90). The prevalence of CKD was 21.9%. Factors significantly associated with an increased risk of CKD included age ≥60 years (OR = 11.70, 95% CI [9.83-15.93]), overweight (OR = 4.19, 95% CI [2.88-6.11]), obesity (OR = 13.31, 95% CI [11.12-15.93]), abdominal obesity (OR = 9.25, 95% CI [7.13-11.99]), AHTN (OR = 20.63, 95% CI [17.02-25.02]), impaired fasting glucose (IFG) (OR = 2.73, 95% CI [2.31-3.23]), type 2 diabetes (T2D) (OR = 14.30, 95% CI [11.14-18.37]), total cholesterol (TC) ≥200 mg/dL (OR = 6.04, 95% CI [5.11-7.14]), triglycerides (TG) ≥150 mg/dL (OR = 5.63, 95% CI 4.76-6.66), HDL-c <40 mg/dL (OR = 4.458, 95% CI [3.74-5.31]), LDL-c ≥130 mg/dL (OR = 6.06, 95% CI [5.12-7.18]), and serum uric acid levels ≥6 mg/dL in women and ≥7 mg/dL in men (OR = 8.18, 95% CI [6.92-9.68]), ( Conclusions: This study underscores the intricate relationship between obesity and CKD, revealing a high prevalence of CKD. Obesity, including overweight, abdominal obesity, AHTN, IFG, T2D, dyslipidemia, and hyperuricemia emerged as significant metabolic risk factors for CKD. Early identification of these risk factors is crucial for effective intervention strategies. Public health policies should integrate both pharmacological and non-pharmacological approaches to address obesity-related conditions and prevent kidney damage directly.

Indexed as

Metabolic SyndromeObesityPrimary Health CareRenal Insufficiency, ChronicAdultAgedAged, 80 and overCross-Sectional StudiesFemaleHumansHypertensionMaleMexicoMiddle AgedPrevalenceRisk FactorsChronic kidney diseaseDyslipidemiaGlomerular filtration rateHyperuricemiaObesityOverweightPrevalenceRisk factors

Identifiers

PMID39099652
PMCPMC11296299

What Socratic holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.