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Exploring the relationship between grip strength and diabetic nephropathy among U.S. adults with type 2 diabetes mellitus: a cross-sectional NHANES analysis

BMC Endocrine Disorders volume 25, Article number: 35 (2025) Cite this article

Abstract

Aim

To examine the relationship between grip strength (GS) and diabetic nephropathy (DN).

Materials and methods

Data on patients with type 2 diabetes mellitus collected between 2011 and 2014 were obtained from National Health and Nutrition Examination Survey (NHANES). Demographic characteristics (sex, age, race, marital status, and educational level), clinical measures (smoking status, drinking status, body mass index [BMI], glycated hemoglobin [HbA1c], urinary albumin creatinine ratio [UACR], diabetes duration, and hypertension), and grip strength assessments were collected. The relationship between GS and DN was analyzed using a logistic regression model. Subgroup analyses were showed as forest plots, conducted while accounting for confounding variables. Restricted cubic splines were applied to investigate nonlinear correlations. A sensitivity analysis was conducted to assess the robustness of the findings.

Results

This study included 1,539 participants. In the multivariate logistic regression model, the odds ratios (ORs) were 0.96 (95% CI, 0.94–0.98) in male and 0.94 (95% CI, 0.91–0.98) in female. Compared with those in the lowest quartiles, participants in the uppermost GS quartiles were less susceptible to DN in male [OR 0.35 (95% CI, 0.20–0.62)] and female [OR 0.37 (95% CI, 0.20–0.67)] (p for trend < 0.001). After adjusting for all variables, the ORs were 0.96 (95% CI, 0.94–0.98) in male and 0.94 (95% CI, 0.91–0.98) in female. Compared with those in the lowest quartiles, participants in the uppermost GS quartiles were less susceptible to DN in male [OR 0.35 (95% CI, 0.20–0.62)] (p for trend < 0.001) and female [OR 0.37 (95% CI, 0.20–0.67)] (p for trend < 0.001). Subgroup analysis demonstrated a reliable connection between GS and DN (all p for interaction > 0.05). We discovered a nonlinear relationship between GS and DN in both male and female participants (all p for nonlinearity < 0.05). More precisely, the data revealed L-shaped relationship and inverted-S relation in male and female participants, respectively.

Conclusion

The results of this cross-sectional study using NHANES data indicated a potential negative association between GS and DN. Additional extensive studies are necessary to elucidate these trends.

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Introduction

Diabetic nephropathy (DN), a major complication of diabetes, is characterized by elevated levels of albumin in the urine and/or a reduced estimated glomerular filtration rate (eGFR) [1]. DN is the primary cause of chronic kidney disease (CKD) in many nations, leading to end-stage renal disease (ESRD), which is characterized by significantly impaired kidney function requiring dialysis or kidney transplantation for survival [2]. Patients with DN have an approximately 30-fold higher risk of all-cause mortality, compared patients with diabetes without DN, posing a significant danger to human health [3]. Thus, identifying the risk factors for DN is crucial for early prevention and intervention.

Grip strength (GS) is an inexpensive and simple assessment tool used to measure muscle strength [4]. In patients with CKD, GS is a crucial prognostic indicator and an independent predictor of renal outcomes [5]. Furthermore, recent findings confirmed that decreased GS is associated with an increased likelihood of developing diabetes, DN, and diabetic foot diseases [6,7,8]. Prior studies have shown that individuals with diabetes who have a higher GS tend to have a reduced risk of cardiovascular disease and overall mortality [9].

Previous study reported that lower GS associated with retinal capillary density decline [10]. A recent Mendelian randomization study demonstrated that GS was negatively associated with risk of DN [11]. However, the relationship between GS and DN in patients with diabetes has not been fully explained by the available evidence. Therefore, the present study analyzed data from a large sample extracted from the National Health and Nutrition Examination Survey (NHANES) to comprehensively evaluate the correlation between GS and the risk of DN in American adults.

Methods

Study population

The NHANES database, created by the National Center for Health Statistics (NCHS), is a nationwide survey aimed at evaluating the health and dietary habits of individuals living outside of institutions in the US. The present study initially considered 2,091 participants with type 2 diabetes mellitus from the NHANES 2011–2014. The exclusion criteria were: (1) current pregnant, (2) age < 20 years, (3) missing data on urinary albumin creatinine ratio (UACR), (4) missing GS data, (5) missing covariate data. Finally, the analyses included 1,538 participants (Fig. 1).

Fig. 1
figure 1

The flow chart of study participants

Full size image

Definition of GS

The NHANES Muscle Strength/Grip Test Procedure Manual provides comprehensive instructions for assessing the GS. Following a brief preparation that involved explaining and demonstrating the protocol, adjusting the grip size of the dynamometer, and completing a practice trial, the participants were instructed to use one hand to squeeze the dynamometer with maximum force and to exhale during the squeeze to prevent buildup of intra-thoracic pressure. Every hand underwent three tests, switching hands between each trial and allowing a 60-s break between measurements on the same hand. GS was defined as the maximum GS of both hands and was expressed in kilograms (kg).

Definition of diabetes and DN

Diabetes was diagnosed when one of the following conditions was met: self-reported diabetes, fasting plasma glucose level ≥ 7.0 mmol/L, glycated hemoglobin (HbA1c) ≥ 6.5%, 2-h OGTT blood glucose ≥ 11.1 mmol/L, random plasma glucose ≥ 11.1 mmol/L, or the use of diabetes medication or insulin. Participants with UACR ≥ 30 mg/g were classified as having DN [1].

Covariates

The demographic parameters included sex, age, race, marital status, and educational level. Additionally, various anthropometric and laboratory covariates were considered, including smoking status, drinking status, body mass index (BMI), HbA1c, diabetes duration, and hypertension.

Smoking status was categorized as “now” for responses of “Every day” or “Some days” to the survey question “Do you now smoke cigarettes”; if the response was “Not at all”, then the participants were asked if they had “Smoked at least 100 cigarettes in life”. Responses of “Yes” and “No” were categorized as “former” and “never”, respectively.

Smoking status was categorized as “now” for a response of “>0” to the survey question “How often have you consumed alcohol over the past 12 mos?”. If the response was “0,” the participants were asked if they “Had at least 12 alcohol drinks/lifetime”; responses of “Yes” and ‘No’ were categorized as “former” and never,” respectively.

Missing responses to the survey question “Age when first told you had diabetes” were recorded as “0”.

Hypertension was defined as the prescription of antihypertensive medications, systolic blood pressure ≥ 140 mmHg, or diastolic blood pressure ≥ 90 mmHg.

Statistical analysis

Demographic features are presented as averages (standard deviation) for continuous variables and proportions (%) for categorical variables. Continuous variables with non-normal distributions are expressed as medians and interquartile ranges and were compared using the Mann-Whitney U test. Categorical variables were analyzed using the chi-square test, whereas normal continuous variables were analyzed using one-way analysis of variance (ANOVA). The relationship between GS and DN was analyzed using a logistic regression model. Subgroup analyses were showed as forest plots, conducted while accounting for confounding variables. Restricted cubic splines were used to investigate nonlinear correlations. The initial 2,091 participants with type 2 diabetes mellitus from NHANES 2011–2014 were included in the sensitivity analysis. Statistical significance was determined by a two-sided P < 0.05. All analyses were conducted using R version 4.4.0.

Results

Table 1 showed the participants’ characteristics according to DN status and sex. Among the 1,538 included participants, 791 (51.4%) were male and 747 (48.6%) were female. Overall, 448 (29.1%) participants had DN, including 239 (30.2%) male and 209 (28.0%) female participants. Male participants with DN were more likely to be older and hypertensive, have a higher BMI, higher HbA1c, longer diabetes duration, and lower GS compared with participants without DN. Female participants with DN were more likely to be older, and have higher proportions of being unmarried, smoking, hypertension, higher HbA1c, longer diabetes duration, and lower GS compared with participants without DN.

Table 1 Baseline characteristics of participants
Full size table

Table 2 showed the results of logistic regression analysis of the association between GS and DN. In model 1, the odds ratios (ORs) were 0.96 [95%confidence interval (CI), 0.94–0.97] for male and the 0.93 (95%CI, 0.91–0.96) for female. Compared with those in the lowest quartiles, participants in the uppermost GS quartiles were less susceptible to DN in both male [OR 0.35 (95%CI, 0.22–0.54)] (p for trend < 0.001) and female [OR 0.30 (95%CI, 0.18–0.48)] (p for trend < 0.001). The relationship between GS and DN remained consistent across various models and the trend was robust. In model 3, after adjusting for all variables, the ORs were 0.96 (95%CI, 0.94–0.98) in male and 0.94 (95%CI, 0.91–0.98) in female. Compared with those in the lowest quartiles, participants in the uppermost GS quartiles were less susceptible to having DN in both male [OR 0.35 (95%CI, 0.20–0.62)] (p for trend < 0.001) and female [OR 0.37 (95%CI, 0.20–0.67)] (p for trend < 0.001). The variance inflation factors (VIF) was shown in Supplementary Table 1. Variables with VIF < 2 showed no collinearity.

Table 2 Logistic regression analysis on the association between GS and DN
Full size table

Figure 2 showed the results of the restricted cubic spline analyses, including the ORs and 95%CIs for the association between GS and DN. A nonlinear relationship between GS and DN was observed in both male and female (all p for nonlinearity < 0.05). More precisely, the associations showed L-shaped and inverted S-shaped relationships in male and female participants, respectively. In male participants, the risk of DN decreased with increasing GS, but when GS went to 35.9 kg, the risk of DN remained essentially unchanged with increasing GS. In female participants, the risk of DN remained essentially unchanged with increasing GS when GS up to 19.3 kg, increased with GS when GS exceeded 19.3 kg up to 34.1 kg, and remained essentially unchanged with increasing GS above 34.1 kg.

Fig. 2
figure 2

Restricted cubic spline of OR and 95% CI for the association between GS and DN (A) Male and (B) Female

Full size image

Figure 3 showed the results of subgroup analysis. The subgroup analysis demonstrated a consistent and reliable connections between GS and DN across various subgroups. Notably, no significant interactions were observed for age, race, marital status, education level, smoking status, drinking status, BMI, HbA1c, diabetes duration, or hypertension, suggesting that the results of the different layers were consistent and reliable (all p for interaction > 0.05).

Fig. 3
figure 3

The association between GS and DN by subgroups

Full size image

Table 3 shows the results of the sensitivity analyses of the association between GS and DN. In model 1, the ORs were 0.96 (95% CI, 0.94–0.97) in male participants and 0.93 (95% CI, 0.91–0.96) in female participants. Compared with those in the lowest quartiles, participants in the uppermost GS quartiles were less susceptible to having DN among both male [OR 0.37 (95% CI, 0.25–0.55)] (p for trend < 0.001) and female [OR 0.27 (95% CI, 0.17–0.42)] (p for trend < 0.001) participants. The relationship between GS and DN remained consistent across various models, and the trend was robust. In model 3, after adjusting for all variables, the ORs were 0.95 (95% CI, 0.93–0.98) in male participants and 0.95 (95% CI, 0.91–0.98) in female participants. Compared with those in the lowest quartiles, participants in the uppermost GS quartiles were less susceptible to DN in both male [OR 0.42 (95% CI, 0.24–0.73)] (p for trend < 0.001) and female [OR 0.35 (95% CI, 0.19–0.64)] (p for trend < 0.001) participants.

Table 3 The sensitivity analysis on the association between GS and DN
Full size table

Discussion

To the best of our knowledge, this is the first study to investigate the association of GS with DN risk in patients with type 2 diabetes mellitus. The results showed that a higher GS was associated with a lower DN risk in both male and female participants. The results of the subgroup analyses demonstrated the stability of this association. The GS had a threshold effect on DN, with the risk of DN no longer decreasing when the GS increased to a certain level.

In a recent study, patients with type 2 diabetes mellitus and sarcopenia had a 1.1-fold increased risk of severe diabetic nephropathy compared with patients without sarcopenia. Compared with the present study, which measured muscle function using GS, the previous study determined sarcopenia according to appendicular skeletal muscle mass (ASM) [12]. Prior research has shown that muscle strength is more crucial than muscle mass for forecasting health outcomes, and it is now widely accepted that muscle strength plays a greater role in determining sarcopenia than muscle mass [13, 14]. The latest recommendation from the European Working Group on Sarcopenia in Elderly Individuals identified weak muscle strength as the primary feature of sarcopenia and suggested GS as a substitute measure for overall strength [15]. Therefore, the current research, utilizing GS, offers a unique advantage in over the previous studies. The results of the present study showed that GS is negatively related to the risk of DN.

The mechanisms linking GS and DN remain poorly understood. Evidence suggests that low GS and DN share several risk factors, and that several pathways link them, such as insulin resistance, chronic inflammation, etc [16,17,18]. On the one hand, muscle is an endocrine organ capable of producing myokines such as irisin, which has been reported to alleviate insulin sensitivity [19, 20]. It was discovered that irisin, produced by muscles, plays a protective role in shielding the kidney from damage caused by diabetes mellitus [21]. Furthermore, higher muscular strength is linked to a lower risk of developing long-term diabetes [22]. As skeletal muscle is the primary location for insulin-facilitated glucose uptake, it could suggest that insulin resistance plays a significant role in the decline of muscle function [23]. On the other hand, some studies indicate that inflammation can contribute to complications such as diabetic retinopathy, nephropathy, and neuropathy [24]. Multiple studies have confirmed the inverse relationship between GS and levels of inflammation [25, 26]. Owing to the similarities in physiopathology between these two conditions, it is challenging to distinguish whether a low GS is the root cause of DN or a resulting complication. Moreover, the association between GS and DN may be bidirectional. Therefore, further studies are required to elucidate these underlying mechanisms.

Targeted comprehensive interventions are crucial owing to the complex progression of DN. Various strategies, including changes in diet, medications, and lifestyle habits, are used to lower the risk of developing DN [1]. Low-protein diets have been proven to be safe and effective, without causing harm to muscle atrophy, muscle mass, or overall health, which is significant. Resistance training can boost muscle strength, leading to better glucose control, lower HbA1c levels, and increased expression of important proteins in the insulin signaling pathway [27]. Resistance training is also successful in decreasing plasma pro-inflammatory markers such as C-reactive protein. Resistance training is anticipated to enhance muscle strength, ultimately leading to a reduction in urinary protein levels. At present, pharmaceuticals to reduce the progression of DN are limited. Possible treatments consist of angiotensin-converting enzyme (ACE) inhibitors, angiotensin II receptor blockers (ARB), sodium-glucose cotransporter − 2 (SGLT-2) inhibitors and novel non-steroidal mineral receptor antagonists [28]. Further investigations are required to elucidate the potential dangers and advantages of these therapies.

Our study has several strengths. This study’s main advantage was being the initial extensive population-based research to uncover the link between GS and DN in American adults. The questionnaire and laboratory datasets contain comprehensive demographic, lifestyle, nutritional, and medical data. Having this information allows us to more effectively manage potential confounding variables in the multivariate regression models. Additionally, the large sample size provided by the NHANES increased the ability to obtain meaningful findings.

Nevertheless, this study has some limitations. For instance, DN was diagnosed using a single UACR test, rather than 3 months of observation. However, as the prevalence of DN in this study was similar to that reported previously, the results are considered reliable. Furthermore, the NHANES utilizes a cross-sectional design, making it difficult to directly assess the causal relationship between GS and DN due to the lack of ability to evaluate temporal relationships in the data. Our population representation was ultimately restricted by the NHANES database. Thus, whether the association between GS and DN applies to other demographic groups remains unclear.

Conclusion

Our research found that higher GS appeared associated with lower risk of DN. Given the research methodology we used, additional extensive prospective studies and clinical trials are necessary to elucidate the relationship’s characteristics and trends.

Data availability

Publicly available datasets were analyzed in this study. Data can be found below: www.cdc.gov/nchs/nhanes/.

References

  1. McGrath K, Edi R. Diabetic kidney disease: diagnosis, treatment, and prevention. Am Family Phys. 2019;99:751–9.

    Google Scholar 

  2. Martinez-Castelao A, Navarro-Gonzalez JF, Gorriz JL, de Alvaro F. The concept and the epidemiology of diabetic nephropathy have changed in recent years. J Clin Med. 2015;4:1207–16.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  3. Sagoo MK, Gnudi L. Diabetic nephropathy: an overview. Methods Mol Biol. 2020;2067:3–7.

    Article  PubMed  CAS  Google Scholar 

  4. Roberts HC, Denison HJ, Martin HJ, Patel HP, Syddall H, Cooper C, et al. A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardised approach. Age Ageing. 2011;40:423–9.

    Article  PubMed  Google Scholar 

  5. Chang YT, Wu HL, Guo HR, Cheng YY, Tseng CC, Wang MC, et al. Handgrip strength is an independent predictor of renal outcomes in patients with chronic kidney diseases. Nephrology, dialysis, transplantation: official publication of the European Dialysis and Transplant Association -. Eur Ren Association. 2011;26:3588–95.

    Google Scholar 

  6. Boonpor J, Parra-Soto S, Petermann-Rocha F, Ferrari G, Welsh P, Pell JP et al. Associations between grip strength and incident type 2 diabetes: findings from the UK Biobank prospective cohort study. BMJ open diabetes research & care. 2021;9.

  7. Oh TJ, Kang S, Lee JE, Moon JH, Choi SH, Lim S, et al. Association between deterioration in muscle strength and peripheral neuropathy in people with diabetes. J Diabetes Complicat. 2019;33:598–601.

    Article  Google Scholar 

  8. Imre E, Kocakgol N, Imre E. Low handgrip strength is associated with diabetic foot disease in geriatric patients with type 2 diabetes. Turk J Med Sci. 2022;52:1854–62.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Celis-Morales CA, Petermann F, Hui L, Lyall DM, Iliodromiti S, McLaren J, et al. Associations between diabetes and both cardiovascular disease and all-cause mortality are modified by grip strength: evidence from UK Biobank, a prospective population-based cohort study. Diabetes Care. 2017;40:1710–8.

    Article  PubMed  Google Scholar 

  10. Zhong P, Liu R, Zhu Z, Huang W, Wang W. Frailty and risk of microvascular disease in adults with prediabetes. Diabetes Metabolic Syndrome. 2024;18:102942.

    Article  PubMed  CAS  Google Scholar 

  11. Ren L, Wang Y, Ju F, Sun M, Gang X, Wang G. Causality between Sarcopenia and diabetic nephropathy: a bidirectional Mendelian randomization study. Front Endocrinol. 2023;14:1188972.

    Article  Google Scholar 

  12. Huang YM, Chen WM, Chen M, Shia BC, Wu SY. Sarcopenia is an independent risk factor for severe diabetic nephropathy in type 2 diabetes: a long-term follow-up propensity score-matched diabetes cohort study. Journal of clinical medicine. 2022;11.

  13. Newman AB, Kupelian V, Visser M, Simonsick EM, Goodpaster BH, Kritchevsky SB, Strength, but not muscle mass, is associated with mortality in the health, aging and body composition study cohort. The journals of gerontology, Series A et al. Biological sciences and medical sciences. 2006;61:72–77.

  14. Wei L, Zeng J, Fan M, Chen B, Li X, Li Y, et al. Associations between handgrip strength and skeletal muscle mass with all-cause mortality and cardiovascular mortality in people with type 2 diabetes: a prospective cohort study of the UK Biobank. J Diabetes. 2024;16:e13464.

    Article  PubMed  Google Scholar 

  15. Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T, et al. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing. 2019;48:601.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Li S, Zhang R, Pan G, Zheng L, Li C. Handgrip strength is associated with insulin resistance and glucose metabolism in adolescents: evidence from National Health and Nutrition Examination Survey 2011 to 2014. Pediatr Diabetes. 2018;19:375–80.

    Article  PubMed  CAS  Google Scholar 

  17. Hojs R, Ekart R, Bevc S, Hojs N. Markers of inflammation and oxidative stress in the development and progression of renal disease in diabetic patients. Nephron. 2016;133:159–62.

    Article  PubMed  CAS  Google Scholar 

  18. Pichler R, Afkarian M, Dieter BP, Tuttle KR. Immunity and inflammation in diabetic kidney disease: translating mechanisms to biomarkers and treatment targets. Am J Physiol Ren Physiol. 2017;312:F716–31.

    Article  CAS  Google Scholar 

  19. Zheng S, Chen N, Kang X, Hu Y, Shi S. Irisin alleviates FFA induced beta-cell insulin resistance and inflammatory response through activating PI3K/AKT/FOXO1 signaling pathway. Endocrine. 2022;75:740–51.

    Article  PubMed  CAS  Google Scholar 

  20. Crujeiras AB, Zulet MA, Lopez-Legarrea P, de la Iglesia R, Pardo M, Carreira MC, et al. Association between circulating irisin levels and the promotion of insulin resistance during the weight maintenance period after a dietary weight-lowering program in obese patients. Metab Clin Exp. 2014;63:520–31.

    Article  PubMed  CAS  Google Scholar 

  21. Lai W, Luo D, Li Y, Li Y, Wang Q, Hu Z, et al. Irisin ameliorates diabetic kidney disease by restoring autophagy in podocytes. FASEB Journal: Official Publication Federation Am Soc Experimental Biology. 2023;37:e23175.

    Article  CAS  Google Scholar 

  22. Wang Y, Lee DC, Brellenthin AG, Sui X, Church TS, Lavie CJ et al. Association of muscular strength and incidence of type 2 diabetes. Mayo Clinic proceedings. 2019;94:643–651.

  23. Ramirez-Velez R, Garcia-Hermoso A, Correa-Rodriguez M, Lobelo F, Gonzalez-Ruiz K, Izquierdo M. Abdominal aortic calcification is associated with decline in handgrip strength in the U.S. adult population >/=40 years of age. Volume 31. Nutrition, metabolism, and cardiovascular diseases: NMCD; 2021. pp. 1035–43.

    Google Scholar 

  24. Nguyen DV, Shaw LC, Grant MB. Inflammation in the pathogenesis of microvascular complications in diabetes. Front Endocrinol. 2012;3:170.

    Article  Google Scholar 

  25. Granic A, Davies K, Martin-Ruiz C, Jagger C, Kirkwood TBL, von Zglinicki T, et al. Grip strength and inflammatory biomarker profiles in very old adults. Age Ageing. 2017;46:976–82.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Smith L, Yang L, Hamer M. Handgrip strength, inflammatory markers, and mortality. Scand J Med Sci Sports. 2019;29:1190–6.

    Article  PubMed  Google Scholar 

  27. Fraser BJ, Blizzard L, Buscot MJ, Schmidt MD, Dwyer T, Venn AJ, et al. The association between grip strength measured in childhood, young- and mid-adulthood and prediabetes or type 2 diabetes in mid-adulthood. Sports Med. 2021;51:175–83.

    Article  PubMed  Google Scholar 

  28. Rando MM, Guthoff M, Tiwari V, Biscetti F. Editorial: Diagnosis, prevention and treatment in diabetic nephropathy. Frontiers in endocrinology. 2022;13:1011665.

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Acknowledgements

We appreciate the staff and participants of the National Health and Nutrition Examination Survey (NHANES).

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Authors and Affiliations

  1. Department of Endocrinology, The Third Affiliated Hospital of Shanghai University, Wenzhou People’s Hospital, Wenzhou, China

    Xue Chen & Yi Lin

  2. Department of Reproductive Medicine, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China

    Weisong Dong

  3. The Third People’s Hospital of Cangnan County, Wenzhou, Zhejiang, China

    Xiuxiu Wen

  4. Zhejiang Key Laboratory of Intelligent Cancer Biomarker Discovery and Translation, The First Affiliated Hospital of Wenzhou Medical University, Ouhai District, Wenzhou, Zhejiang, China

    Yidan Zuo

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Contributions

Xue Chen drafted of manuscript. Weisong Dong collected the data. Xue Chen, Xiuxiu Wen and Yi Lin analyzed and interpretated the data. Yi Lin revised the article. Yidan Zuo designed the study and revised the article. All authors reviewed the manuscript.

Corresponding author

Correspondence to Yidan Zuo.

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The study protocol was approved by the NCHS Ethics Review Board (https://www.cdc.gov/nchs/nhanes/irba98.htm), and was performed in accordance with the Declaration of Helsinki, with all NHANES participants providing their written informed consent.

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The authors declare no competing interests.

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Chen, X., Lin, Y., Dong, W. et al. Exploring the relationship between grip strength and diabetic nephropathy among U.S. adults with type 2 diabetes mellitus: a cross-sectional NHANES analysis. BMC Endocr Disord 25, 35 (2025). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12902-025-01862-y

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BMC Endocrine Disorders

ISSN: 1472-6823

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