Next Article in Journal
Effects of Brain-Computer Interface-Controlled Hand Robot Training on Post-Stroke Recovery of Upper Limb Motor Functions: A Meta-Analysis of Dose-Matched Randomized Controlled Trials
Previous Article in Journal
Biomarkers for Predicting Clinical Deterioration in Schizophrenia-Spectrum Disorders: A Systematic Review
Previous Article in Special Issue
Targeting Sigma-1 and Sigma-2 Receptors in Neuropathic Pain: Pharmacology, Ligand Development, and Translational Progress
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Brain Sciences
Volume 16
Issue 6
10.3390/brainsci16060551
brainsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Systematic Review

A Systematic Review of Lifestyle Interventions for Neuropathy and Neuropathic Pain: Alcohol Consumption and Avoidance

by
Michael Klowak
1,
Ezra J. Bado
2,
Aquilla Reid-John
2,
Rumaysa Dawood
2,
Candice Madakadze
2 and
Andrea K. Boggild
1,2,3,*
1
Institute of Medical Science, University of Toronto, Toronto, ON M5S 1A1, Canada
2
Tropical Disease Unit, Toronto General Hospital, Toronto, ON M5G 2C4, Canada
3
Department of Medicine, University of Toronto, Toronto, ON M5S 3H2, Canada
*
Author to whom correspondence should be addressed.
Brain Sci. 2026, 16(6), 551; https://doi.org/10.3390/brainsci16060551
Submission received: 15 April 2026 / Revised: 11 May 2026 / Accepted: 12 May 2026 / Published: 22 May 2026
(This article belongs to the Special Issue Cellular and Molecular Mechanisms of Neuropathic Pain)
Browse Figures
Versions Notes

Highlights

What are the main findings?
  • Alcohol consumption and dependence were associated with increased incidence, prevalence, and/or severity of neuropathy/neuropathic pain across observational studies, with over half of included studies demonstrating statistically significant positive associations.
  • Pooled analysis showed higher odds of neuropathy with alcohol exposure (consumption: OR 1.29 95% CI [1.10–1.50]; dependence: 1.24 [1.16–1.33]), while longer duration and greater exposure were linked to increased severity and diminished electrophysiological function, and abstinence was associated with clinical improvement.
What are the implications of the main findings?
  • Findings support a potential contributory role of alcohol use, particularly dependence and chronic exposure, in the development and progression of neuropathy/neuropathic pain, consistent with known neurotoxic and metabolic mechanisms.
  • Alcohol abstinence and reduction may represent a low-risk, low-cost, adjunctive strategy for improving neuropathy/neuropathic pain outcomes, although causal inference is limited by heterogeneity and very low certainty of evidence, highlighting the need for robust interventional studies.

Abstract

Background: Neuropathy and neuropathic pain (NP) are globally prevalent, remain difficult to manage, and are often exacerbated by underlying lifestyle factors. Alcohol use, particularly in the context of chronic consumption or dependence, is a recognized contributor to peripheral nerve damage, yet its association with neuropathy/NP has not been systematically evaluated. This systematic review synthesizes the current evidence on alcohol exposure, including quantity, frequency, and dependency, and its association with the incidence, prevalence, and severity of neuropathy/NP. Methods: This systematic review included observational studies assessing alcohol consumption patterns or dependence in relation to neuropathy/NP outcomes and was conducted in accordance with PRISMA guidelines. Exposure types were analyzed independently, and pooled odds ratios and relative risks were generated when sufficient data were available. The review was registered with PROSPERO number CRD42023484158. Results: Following de-duplication and exclusions, 76 studies were included, comprising cohort (n = 15), case–control (n = 12), and cross-sectional (n = 49) designs. While associations varied by study design and exposure category, alcohol dependence and consumption were more consistently linked with increased neuropathy incidence and severity, including electrophysiological evidence of compromised function. Notably, in studies examining alcohol cessation, abstinence was linked to clinical improvements in neuropathy/NP symptoms such as hypoesthesia and muscle weakness. While heterogeneity and risk of bias were present, largely due to the subjective classification of alcohol exposure and a lack of universally applied objective neuropathy measurement tools, multiple pooled estimates reached statistical significance. Conclusions: Evidence from observational studies supports an association between alcohol use, especially dependence, and the development and progression of neuropathy/NP, although causality remains unproven. Abstinence may offer therapeutic benefit, though further abstinence- and/or harm reduction-related interventional studies are required to clarify causality and guide low-cost, adjunctive strategies for alcohol-related neuropathy/NP.

1. Introduction

Neuropathy and neuropathic pain (NP), caused by lesions or diseases of the nervous system, are conditions of increasing global relevance, with up to 10% of individuals worldwide suffering from their debilitating effects [1]. Alcohol-related neuropathy remains a significant contributor to this burden, as recent estimates indicate it may account for 8–10% of polyneuropathies across all populations [2]. Patients with alcohol use disorders (AUDs) already experience substantial morbidity, due in part to alcohol-related neurological disability, further complicating its impact on the overall healthcare system [3]. Comprehensive systematic reviews and epidemiological data suggest that neuropathy/NP conditions are prevalent in up to 66% of all individuals with chronic alcohol use disorders [2,3]. As a result, this relationship underscores the significant and persistent social and financial burden that neuropathy/NP exerts at an individual and population level. It is estimated that costs associated with harmful alcohol use, including alcohol-related neuropathies, account for roughly 1–2% of the global GDP [4]. Given this substantial negative physical and economic impact, there is a dire need for supportive therapies that more effectively address the symptomatology of alcohol-related neuropathies.
The neuropathophysiology associated with chronic and excessive alcohol use is highly insidious, characterized by slow and progressive neurological degeneration [5]. Over the course of months to years, alcohol users develop distal pain, numbness, diminished reflexes, impaired vibration perception, and motor/sensory electrophysiological abnormalities, typically affecting the lower and upper limbs [2,6]. The pathogenesis of alcohol-related neuropathy/NP involves both direct and indirect mechanisms. Indirectly, chronic and excessive alcohol consumption contribute to nutritional deficiencies, including reducing hepatic storage of thiamine, limiting phosphorylation, and impairing absorption. These metabolic disruptions, compounded by the poor caloric intake commonly associated with alcohol use disorders, ultimately lead to peripheral nervous system sensitization and degeneration [5,6]. Likewise, excessive ethanol metabolism produces reactive oxygen species and other cytotoxic byproducts that significantly damage and impair nerve cells. Therefore, the direct effects of ethanol consumption further contribute to peripheral nerve injury, leading to primary axonal damage and secondary demyelination of motor and sensory fibers [5,6]. Emerging evidence also suggests that alcohol may alter microRNA expression, thereby influencing neural signaling involved in pain processing, with growing interest in their role as biomarkers in neuropathic conditions [7,8]. While these mechanisms represent the primary pathways identified to date, preclinical studies continue to investigate additional molecular and neuroimmune processes [5]. Despite this, effective management of neuropathic symptoms remains limited, and additional adjunctive treatment strategies targeting these underlying mechanisms are needed.
Conventional pharmacologic therapies for neuropathy/NP, including antidepressants, anticonvulsants, and opioids, remain only somewhat effective, typically providing less than 30% pain relief [1]. In the context of alcohol-related neuropathy/NP, additional nutritional support and adjunctive therapies have also been explored beyond gold standard pharmaceuticals. Vitamin supplementation, including thiamine, B6, and B12, as well as antioxidant compounds such as alpha-lipoic acid and N-acetylcysteine may confer protective effects, limiting overall morbidity [2,5,6]. Likewise, lifestyle interventions and/or modifications, including domains such as nutrition, physical activity, stress management, sleep, social connectedness, and avoidance of harmful substances (e.g., tobacco and alcohol), have recently emerged as low-risk, cost-effective strategies for reducing the overall morbidity of neuropathy/NP due to various etiologies [9]. Specifically, modification of alcohol consumption, including reduction or abstinence, has been shown to successfully manage neuropathy and NP symptoms; however, evidence remains limited given the insidious nature of alcohol dependence and addiction [2]. As part of an ongoing systematic review series, we have examined individual lifestyle domains independently in relation to neuropathy/NP, including diet and tobacco use [2,9,10]. Building on this framework, the present review specifically seeks to assess how alcohol consumption (including frequency, quantity, and duration) impacts the incidence, prevalence, and severity of neuropathy and NP. Ultimately, it is hypothesized that alcohol use meaningfully contributes to disease burden, and that cessation may help reduce overall morbidity.

2. Materials and Methods

The “Preferred Reporting Items for Systematic Reviews and Meta-Analysis” (PRISMA) guidelines/checklist were followed (Table S1), and the review was prospectively registered with the International Prospective Register of Systematic Reviews (PROSPERO: CRD42023484158). Interventional and observational studies, including cohort, case–control, and cross-sectional designs, were included if they assessed lifestyle variables as interventions, exposures, outcomes, or stratification factors in populations with neuropathy and/or neuropathic pain, regardless of etiology. The search spanned from database inception to 21 October 2025. This work is part of a larger systematic review series on lifestyle interventions and neuropathy/neuropathic pain and specifically evaluates alcohol consumption, dependence, and related exposures. Detailed methodology for the overarching systematic review series, including full eligibility criteria, outcome measures, data sources, search strategy, study selection, data extraction, statistical analysis, risk of bias and certainty of evidence assessments, and meta-analyses, have been previously reported and are available in open-access format [9,11].
In brief, the following comprehensive search strategy was applied across multiple databases (including Medline, PubMed, Scopus, Embase, and LILACS): (neuropathic pain OR neuropathy OR neuritis OR diabetic neuropathy OR peripheral neuropathy OR chemical neuropathy OR toxic neuropathy OR chemotherapy-induced peripheral neuropathy OR vitamin B deficiency) AND (nutrition OR nutrient OR nutritionally compromised OR micronutrient OR macronutrient OR malnutrition OR nutritional status OR nutrient supplement* OR plant based OR vegetarian OR vegan OR mediterranean diet OR diet OR physical activity OR exercise OR lifestyle OR lifestyle interventions OR BMI OR smoking OR alcohol OR stress OR sleep). Records were independently screened by two reviewers using Covidence. Eligibility was defined using a PICO-based framework, including individuals with neuropathy or NP of any etiology, with alcohol-related exposures assessed against non-exposed groups, and outcomes encompassing incidence, prevalence, and severity. From included studies, data were extracted on study characteristics, exposure definitions, and neuropathic outcomes at the highest level of detail reported, enabling pooled estimates to be calculated where appropriate. Study quality was then appraised using Joanna Briggs Institute-based risk of bias tools, alongside evaluation of certainty of evidence using the GRADE (“Grading of Recommendations, Assessment, Development, and Evaluation”) framework. These data were subsequently synthesized through meta-analyses using stratified exposure categories, with odds ratios and relative risks calculated and pooled where feasible.

Statistical and Meta-Analyses

Alcohol exposure was stratified to capture differences in reported consumption patterns and dependency, including consumption status (never, former, current, or any use/history of use), dependency-related measures (addiction, AUD, abuse, or excessive consumption), and guideline-based thresholds (e.g., >30 g/day or exceeding sex-specific recommendations such as >7/14 or >14/21 units for females/males). Given anticipated heterogeneity in exposure definitions, classifications ranged from simple dichotomous measures (e.g., consumption yes/no) to more detailed categorizations and broad quantitative estimates, including intake reported as drinks, grams, or units per day or week, with variability in how thresholds and units were defined across studies. Where exposure categories combined former, current, lifetime, or unspecified alcohol use, these classifications were retained as reported, but interpreted as broad exposure categories, as timing of exposure could not be consistently distinguished across studies. Some exposure categories were defined broadly enough to include individuals with prior alcohol use, potentially leading to misclassification, and adding variability to pooled results. To mitigate this, data were captured at the most detailed level available from each study to enable more refined stratified analyses.
Although included studies specified neuropathy subtypes and underlying etiologies, there was insufficient overlap within individual etiologic subgroups to support meaningful subgroup-specific pooled analyses. As such, neuropathy and NP outcomes were pooled within study design and exposure strata to preserve analytic stability, while etiologic heterogeneity was considered during interpretation and certainty of evidence assessment. Studies enrolling alcohol-dependent populations or individuals with alcohol-related neuropathy were retained, as they contributed relevant data on neuropathy/NP incidence, prevalence, severity, electrophysiological impairment, and response to abstinence, but were interpreted within the context of their underlying study populations and exposure definitions, and not as independent estimates of alcohol as a causal risk factor. Pooled estimates were generated only when studies of the same design reported sufficiently comparable alcohol exposure classifications and neuropathic outcomes. Given the observational nature of the included literature, particularly among cross-sectional studies, temporality between alcohol exposure and neuropathy/NP outcomes could not always be established. Accordingly, pooled estimates reflect associations across heterogenous populations and study designs rather than causal effect estimates, and these methodological constraints were incorporated into risk of bias and certainty of evidence assessments using the GRADE framework to inform interpretation of the synthesized results.

3. Results

3.1. Literature Search

The search strategy identified 23,285 articles across five databases, including Embase (8579), PubMed (5254), Medline (4769), Scopus (4667), and LILACS (0), with 17 additional articles captured via bibliography screening. Following deduplication, 16,373 records remained, of which 1023 full-text articles were assessed for final inclusion. A total of 367 records described primary outcomes relevant to the systematic review series, of which 76 reported alcohol use in the context of neuropathy or neuropathic pain (Table 1). A comprehensive summary of the screening process and reasons for article exclusion is available in Figure 1.

3.2. Included Studies

Records identified in this systematic review were all observational in nature. Fifteen cohort studies were included, comprising 252,171 participants, with participant numbers ranging from 10 to 222,334 per study [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26]. Participant ages ranged from 18 to 90 years across the cohort studies, with females comprising 48.44% of the collective sample. Most studies were conducted in high-income settings, with the exception of one study from Zimbabwe, as classified by the World Bank [23]. Publication years spanned 1982 to 2025. The majority of the cohort studies investigated populations with peripheral neuropathy (PN) (7) [13,15,17,18,20,25,26], or broadly defined neuropathy (6) [12,19,21,23,24], with fewer examining polyneuropathy (PoN) (2) [14,16], and complex regional pain syndrome (CRPS) (1) [22]. Neuropathy etiologies were predominantly diabetes mellitus (7) [12,13,14,15,19,21,24], cancer (4) [20,23,25,26], and alcohol dependence (3) [17,18,19], as well as trauma and HIV (1 each) [16,22]. Cohort studies all reported neuropathy status in relation to alcohol exposure, categorized as any consumption (7) [13,15,20,22,23,25,26], alcohol dependence (6) [12,16,17,18,19,21], or consumption by guidelines (2) [14,24]. However, only eight studies [12,13,14,19,21,22,24,25] provided sufficient data to calculate odds ratios and relative risks for neuropathy incidence among exposed versus non-exposed groups.
Across 12 case–control studies, 1481 cases and 2441 controls were analyzed, with sample sizes spanning 18 to 1156 individuals per study [27,28,29,30,31,32,33,34,35,36,37,38]. The mean age ranged from 27 to 77 years, with females comprising 45.9% of total participants. Publication date ranged from 1970 to 2023, and most studies were conducted in high-income countries, aside from one from Ethiopia [32]. PN (4) [27,32,36,38] and ulnar neuropathy of the elbow (3) [31,35,37] were the most commonly studied conditions, with additional cases of chronic inflammatory demyelinating polyradiculoneuropathy (CIDP), small fiber neuropathy (SFN), distal symmetric neuropathy (DSN), PoN, and general neuropathy (1 each) [28,29,30,33,34], attributed to any etiology (5) [28,29,31,35,37], alcohol dependence (4) [27,33,36,38], or diabetes mellitus (3) [30,32,34]. Alcohol exposure was categorized as any consumption (7) [28,30,31,32,34,35,37] and alcohol dependence (5) [27,29,33,36,38]. Six studies [28,29,30,32,35,36] reported sufficient data to calculate odds ratios for the association between alcohol exposure and neuropathy.
Forty-nine cross-sectional studies were included, encompassing 90,889 participants, with study sizes ranging from 18 to 25,710 individuals [39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87]. Participant ages spanned 15 to 100 years, with females accounting for 43.75% across studies. One ecological cross-sectional study evaluated insurance reimbursement claims per 1000 population, covering up to 126 million individuals, and was excluded from these averages [68]. Publications spanned 1965 to 2024 and included both high- (43/49) [39,40,41,42,43,44,45,46,48,50,51,52,53,54,55,56,57,59,60,61,62,63,64,65,66,67,68,69,70,71,72,76,77,78,79,80,81,82,83,84,85,86,87] and low-income (6/49) [47,49,58,73,74,75] countries. PN (29) [39,40,41,46,47,48,49,52,53,54,57,59,61,62,64,66,67,70,71,72,73,74,75,76,77,78,80,83,85] accounted for over half of the diagnoses across all studies, followed by PoN (8) [44,50,56,63,79,81,84,86], painful neuropathy (6) [42,51,60,65,68,82], and general neuropathy (6) [43,45,55,58,69,87] to a lesser extent. Alcohol dependence (22) [40,41,44,47,50,52,53,54,61,64,66,67,69,71,74,78,79,81,82,85,86,87] and diabetes mellitus (14) [39,43,46,49,56,57,58,59,60,62,73,77,80,84] were the most frequently reported etiologies, followed by any cause (8) [42,48,51,55,63,65,68,83], cancer (4) [70,72,75,76], and BMI (1) [45]. Alcohol exposure was categorized as any consumption (25) [39,42,43,45,46,48,49,51,54,57,58,59,62,63,64,68,70,72,73,74,75,76,81,83,84], alcohol dependence (22) [40,41,44,47,50,52,53,55,60,61,65,66,67,69,71,78,79,80,82,85,86,87], and overconsumption by guidelines (2) [56,77]. Prevalence estimates of neuropathy were reported in relation to alcohol exposure in 17 [39,42,43,46,48,51,56,57,58,59,67,70,73,77,80,84,85] studies, with odds ratios used to quantify the strength of these associations.

3.3. Risk of Bias

Risk of bias among cohort studies was predominantly moderate, with low risk identified in 56% (42/75) of assessed measures. Information and attrition biases were most prominent, as most studies relied on non-objective outcomes (14/15, 93%) [12,13,14,15,16,17,19,20,21,22,23,24,25,26] and reported moderate to high loss to follow-ups (10/15, 67%) [12,14,15,16,17,18,20,22,24,25], while selection, confounding, and outcome biases were generally low (0/15, 0%; 5/15, 33% [17,18,22,23,26]; 4/15, 27% [17,20,22,25], respectively) (Figure 2).
Case–control studies demonstrated an overall moderate risk of bias, with 54% (26/48) of domains rated as low-risk. Poor matching of cases and controls represented the most prominent limitation (10/12, 83%) [28,29,30,32,33,34,35,36,37,38], while sampling/selection, detection, and confounding biases were less prevalent (3/12, 25% [27,33,38]; 5/12, 42% [27,28,31,33,38]; 4/12, 33% [28,29,33,38], respectively) (Figure 3).
Comparatively, cross-sectional studies were associated with a higher risk of bias overall, with just 33% (32/98, 33%) of assessed domains classified as low-risk. Statistical adjustments were adequate in most studies (29/49, 59%) [39,42,43,45,46,48,49,51,53,55,56,57,59,60,67,68,69,70,71,72,76,77,78,80,81,83,84,86,87]; however, information bias remained a major concern due to the widespread use of non-objective outcomes (46/49, 94%) [39,40,41,42,43,45,46,47,48,49,50,51,52,53,54,55,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,86,87]. Only one study [56] achieved an overall low risk of bias, whereas the vast majority (75/76, 99%) had at least one domain classified as unclear or high risk (Figure 4).

3.4. Summary of Findings

Quantitative and qualitative synthesis of neuropathy and NP incidence, prevalence, and association with alcohol consumption is available in Table 1 and Table 2. Of the seven cohort studies assessing alcohol consumption and neuropathy/NP, only one (14%) reported a significant positive association between alcohol consumption and higher pain intensity [22] (Table 1). Five studies (71%) found no significant association [13,20,23,25,26], and one study (14%) reported significantly lower odds of neuropathy with more frequent alcohol consumption [15] (Table 1). Collectively, three studies (43%) provided sufficient data for pooled analysis. Among these, the pooled odds of a neuropathic outcome in those exposed vs. unexposed (i.e., odds ratio) was 1.29 [95% confidence interval 1.10–1.50], indicating 29% higher odds of incident neuropathy, while the pooled relative risk was 1.14 [1.05–1.23] [13,22,25] (Table 2, and Figure 5).
Of the six cohort studies assessing alcohol dependence and neuropathy/NP, four (67%) reported a significant positive association, either with increased odds of incident neuropathy [12,19], or with clinical and electrophysiological improvement with alcohol abstinence [17,18] (Table 1). The remaining two studies (33%) did not report a significant association [16,21] (Table 1). Overall, three studies (50%) provided sufficient data for pooled analysis. Among these, the pooled odds ratio was 1.24 [1.16–1.33], and the pooled relative risk was 1.19 [1.12–1.25], suggesting that individuals with AUD, or who were dependent on alcohol, had 24% higher odds of incident neuropathy compared to non-dependent or abstinent individuals [12,19,21] (Table 2, and Figure 6).
The remaining cohort studies focused on alcohol overconsumption by specific guidelines. Alcohol consumption in excess of guideline recommendations (that is, of >14/21 units per week for females/males) was significantly associated with increased prevalent NP [14], while consumption >30 g per week was not [24] (Table 1). The calculated odds ratio was 1.51 [1.04–2.2], indicating a 51% increased risk of neurophysiological deterioration and pain in those exceeding thresholds compared to those who are not. The calculated relative risk was 1.31 [1.02–1.71] (Table 2 and Figure 7).
Seven case–control studies assessed alcohol consumption and neuropathy/NP, of which only one study [32] (14%) reported significantly greater alcohol consumption in cases versus controls, while six studies [28,30,31,34,35,37] (86%) did not report a significant difference (Table 1). In this subset, four case–control studies (57%) provided sufficient data to calculate a pooled odds ratio of 0.82 [0.73–0.92], suggesting 18% lower odds of neuropathic outcomes in cases versus controls [28,30,32,35] (Table 2 and Figure 8).
The remaining five case–control studies assessed alcohol dependence and neuropathy/NP. Of these, four studies (80%) reported a significant positive association, either with a greater prevalence of alcohol dependence, parental history of alcoholism, and higher weekly alcohol consumption among those with neuropathy [36], longer duration of alcohol dependence, and larger total lifetime dose of alcohol [27], or with diminished electrophysiological measures of nerve function in individuals with a history of heavy alcohol consumption, including reduced sensory and motor nerve conduction velocities, amplitudes, latencies, and fiber densities [33,38]. The fifth study (20%) did not report significant findings [29]. Among these, two case–control studies (40%) provided sufficient data to calculate a pooled odds ratio of 1.24 [0.73–2.15], indicating no clear association [29,36] (Table 2 and Figure 9).
Of the 25 cross-sectional studies reporting alcohol consumption and neuropathy/NP, ten (40%) reported a statistically significant positive association [39,54,62,63,64,68,70,73,74,81]. Neuropathy prevalence was significantly higher in individuals with high to excessive alcohol consumption, a longer history of alcohol consumption, and chronic alcoholism [39,68,70,73,74,81], with stronger associations observed in those with shorter diabetes duration and type II fiber atrophy [54,62]. Heavy alcohol consumption, defined as >4 drinks per day, and binary self-reported indicators of alcohol-related harm, including seeking professional help for alcoholism, withdrawal symptoms, and social/legal issues, were also associated with significant electrophysiological perturbations [63,64] (Table 1). In contrast, three cross-sectional studies (12%) reported a statistically significant protective association, where moderate alcohol consumption was linked to lower neuropathy prevalence [43,59], or decreased monofilament insensitivity [83], while another study (4%) found that former alcohol consumption was associated with greater neuropathy prevalence compared to current consumption [84] (Table 1). The remaining eleven cross-sectional studies (44%) did not report a statistically significant association [42,45,46,48,49,51,57,58,72,75,76]. Cumulatively, twelve studies (48%) provided sufficient data to calculate a pooled odds ratio of 0.50 [0.48–0.53], corresponding to 50% lower odds of prevalent neuropathy among those reporting alcohol exposure compared to non-use [39,42,43,46,48,51,57,58,59,70,73,84] (Table 2 and Figure 10).
Of the 22 cross-sectional studies reporting alcohol dependence and neuropathy/NP, 18 (82%) reported a statistically significant positive association [40,41,44,47,50,52,53,61,66,67,69,71,78,79,82,85,86,87]. Longer durations of alcohol consumption and alcohol dependence were associated with greater neuropathy severity [47,53,79,82,86,87] and significantly diminished electrophysiological responses [40,41,44,50,52,61,66,67,69,71,78,85] (Table 1). Of the remaining four (18%) cross-sectional studies, three (14%) identified a significantly lower prevalence of alcohol dependence among individuals with neuropathy [55,60,80], while one study (5%) reported alcohol dependence in 6.36% of individuals with neuropathy but did not provide further statistics [65] (Table 1). Cumulatively, three studies provided sufficient data to calculate an odds ratio of 0.60 [0.54–0.67], suggesting that alcohol exposure is associated with 40% lower odds of prevalent neuropathy compared to non-use [67,80,85] (Table 2 and Figure 11).
The final two cross-sectional studies assessed alcohol consumption using specific guideline-based thresholds (>14/7 units per week for males/females), and did not report a significant association individually. However, pooled analysis yielded an odds ratio of 1.21 [1.06–1.39], corresponding to 21% higher odds of prevalent neuropathy [56,77] (Table 1 and Table 2, and Figure 12).

4. Discussion

Findings from this systematic review suggest that varying degrees of alcohol consumption are associated with neuropathy and NP across observational study designs; however, these associations should be interpreted in the context of substantial heterogeneity in neuropathy etiologies and alcohol exposure definitions, and do not represent causal effect estimates. Over half (39/76, 51.3%) of included studies demonstrated a statistically significant positive association, whereby alcohol consumption increased the incidence, prevalence, and/or severity of neuropathy or neuropathic pain (including chemotherapy-induced PN, diabetic PoN, PN, PoN, somatic neuropathy, and UN) across a wide range of etiologies, such as diabetes, cancer, and AUD (p < 0.05) [12,14,17,18,19,22,27,32,33,36,38,39,40,41,44,47,50,52,53,54,61,62,63,64,66,67,68,69,70,71,73,74,78,79,81,82,85,86,87]. Conversely, 29/76 (38.2%) studies reported no association [13,16,20,21,23,24,25,26,28,29,30,31,34,35,37,42,45,46,48,49,51,56,57,58,65,72,75,76,77], while only 8/76 (10.5%) demonstrated a statistically significant negative effect (p < 0.05) [15,43,55,59,60,80,83,84]. Across all study designs, the overall certainty of evidence was very low, largely driven by substantial risk of bias, particularly due to reliance on self-reported alcohol exposure, as well as heterogeneity in exposure classification and outcome assessments (Figure 2, Figure 3 and Figure 4, Table 2). Despite these limitations, a significant positive association was still observed in downstream pooled analyses, consistent with the previously published literature demonstrating a high prevalence of neuropathy among those with chronic alcohol use, with estimates approaching 46%, alongside increased pain sensitivity and interference associated with heavy alcohol use and withdrawal [2,10]. Likewise, these findings align with the previously described pathophysiological mechanisms of alcohol-related neuropathy, whereby chronic and excessive alcohol use contribute to peripheral nerve injury through both direct neurotoxic effects, indirect metabolic disruptions, and potential molecular regulatory processes. Together, ethanol-induced oxidative stress and alcohol-related nutritional deficiencies may drive peripheral nervous system sensitization and degeneration, thereby explaining the increased incidence, prevalence, and severity of neuropathy and neuropathic pain observed in this review.

4.1. Cohort Studies

Cohort studies demonstrated the most consistent positive estimated effects of alcohol exposure on incident neuropathy outcomes pooled across all study designs, corresponding to 29% higher odds with any alcohol consumption compared to non-use [13,22,25]. These findings contrast those of the individual studies, which largely reported no significant association between alcohol consumption and neuropathic outcomes [13,20,23,25,26], or demonstrated an inverse effect [15,22]. Despite this, a subset of studies [13,25] reporting no association contributed point estimates above the null, which when pooled ultimately shifted the overall effect toward a statistically significant positive relationship (Figure 5). Due to this lack of directional concordance across studies, there was a high risk of inconsistency. Together, with a serious risk of bias, and low risk of imprecision and indirectness, the overall certainty of evidence remained very low (Table 2). However, these findings suggest that while individual studies may lack power or consistency, pooled analyses may better capture the underlying association between alcohol consumption and incident neuropathy.
Alcohol use disorder and dependence were associated with 24% higher odds of incident neuropathy [12,19,21], aligning with published studies reporting a higher risk of incident neuropathy with AUD overall [12,19], as well as improvements in electrophysiological parameters following abstinence [17,18]. Among the remaining articles, null associations may reflect either the presence of stronger competing risk factors that attenuate the detectable effect of alcohol exposure [16], or study designs in which alcohol-related risk is evaluated relative to already high-risk comparator groups, thereby limiting the ability to detect incremental effects [21]. Notably, cohort studies assessing alcohol dependence contributed some of the most robust evidence within this review, with comparatively fewer concerns related to inconsistency, indirectness, and imprecision (Table 2). However, the overall certainty of evidence remained very low due to inherent limitations of observational designs, including residual confounding and reliance on self-reported alcohol exposure, increasing the overall risk of bias.
The remaining cohort studies assessed alcohol consumption according to predefined guideline thresholds, including exceeding 14/21 units of alcohol per week for females/males [14], or consuming greater than 30 g per week irrespective of sex [24]. The findings of each individual study varied; however, the pooled effects estimate suggests a 51% increased risk of incident neuropathy/NP in those exceeding recommended guidelines versus those who are not [14,24]. The overall certainty of evidence was very low, downgraded due to moderate concerns with indirectness, reflecting arbitrary threshold-based exposure definitions, and imprecision, due to a limited number of contributing studies and wide confidence intervals (Table 2). Overall, pooled analyses across cohort studies suggest that increasing alcohol consumption and dependence are associated with a higher risk of incident neuropathy and related outcomes. However, substantial heterogeneity in underlying etiologies, exposure classification and quantification, and outcome measurement limits the generalizability of pooled effect estimates, which are often derived from restricted subsets of the available data. Likewise, although concerns related to inconsistency, indirectness, and imprecision were generally modest, the overall certainty of evidence remained very low due to a serious risk of bias from subjective outcome measures and substantial loss to follow-up (Table 2). As such, there is a clear need for more robust study designs, including those incorporating objective outcome measures, standardized and quantitative exposure assessments, and improved longitudinal follow-up, to more accurately estimate this relationship.

4.2. Case–Control Studies

The estimated effect of alcohol consumption on neuropathy/NP in case–control studies was highly variable. Despite the majority of studies reporting no specific association [28,30,31,34,35,37], the pooled estimate suggests that cases, or those who endorse consuming any alcohol, have 18% lower odds of neuropathic outcomes compared to controls [28,30,32,35]. Effect estimates across studies largely clustered around the null and were susceptible to unadjusted confounding [28,30,35]. Alcohol consumption was consistently assessed as a secondary exposure rather than a primary variable of interest, and robust multivariable analyses were often not performed, limiting the ability to isolate its independent effect from other lifestyle factors such as smoking, diet, and physical activity. Furthermore, the only study reporting a positive association [32] was imprecise, with wide confidence intervals, resulting in reduced weighting in the pooled analysis. Together, these factors suggest that the observed inverse pooled estimate does not reflect a true protective relationship but rather arises from residual confounding and imprecision in the contributing studies. Given the known risk of bias inherent to observational studies, along with moderate to high concerns related to inconsistency, indirectness, and imprecision, the overall certainty of evidence remained very low (Table 2).
Similarly, no clear association was identified for the effect of alcohol dependence on neuropathy/NP [29,36]. Although the majority of studies reported a statistically significant positive association [27,33,36,38], including greater peripheral neuropathy prevalence and impaired electrophysiological parameters in those with a history of heavy alcohol use or dependence, only two studies provided sufficient data for pooled analysis [29,36], one of which reported no association at all [29]. As a result, the pooled effect estimate remained inconclusive, and the limited number of contributing studies and variability in exposure and outcome assessments resulted in moderate levels of indirectness and imprecision. Despite a non-serious risk of bias and low inconsistency, the overall certainty of evidence was downgraded to very low (Table 2). As such, these findings highlight the need for more robust studies to better estimate these relationships.

4.3. Cross-Sectional Studies

The pooled estimates for both the effect of alcohol consumption and dependence on the prevalence of neuropathy/NP indicate a protective effect, whereby alcohol use is associated with 50%, and 40% lower prevalence of neuropathy compared to non-use, respectively [39,42,43,46,48,51,57,58,59,67,70,73,80,84,85]. This directly contradicts the majority of studies (28/47, 60%) reporting greater prevalence of PN, diabetic PN, chemotherapy-induced PN, PoN, and NP, with greater duration, and frequency of alcohol consumption and dependence [39,40,41,44,47,50,52,53,54,61,62,63,64,66,67,68,69,70,71,73,74,78,79,81,82,85,86,87]. Given the cross-sectional nature of this subset of the literature, a causal relationship cannot be established, as exposure and outcome are assessed simultaneously without accounting for temporal sequence. This enables reverse causation to influence the observed associations, specifically protopathic bias within this body of the literature, whereby individuals with neuropathy may reduce or cease alcohol consumption, resulting in a disproportionate representation of affected individuals within lower-exposure categories. Similarly, survivorship and selection effects may further distort this relationship, as individuals with more severe disease or higher levels of alcohol exposure may be less likely to participate due to physical, cognitive, or psychosocial limitations. Together, these mechanisms may reflect or exaggerate underlying U-shaped relationships, whereby moderate alcohol consumption appears protective relative to both abstinence and heavy use, while also exaggerating inverse associations in pooled analyses. The majority of studies reporting a negative and seemingly protective effect emphasize these phenomena as key limitations within their own analyses [43,59,60,84]. Given these methodological constraints, and the serious risk of bias inherent to cross-sectional designs, the overall certainty of evidence remained very low (Table 2).
Lastly, pooled estimates from the remaining cross-sectional studies examining alcohol consumption per guideline thresholds suggest that intake exceeding 7/14 units per week for females/males is associated with a 21% higher prevalence of neuropathy/NP compared to lower consumption [56,77]. However, individual study results were non-significant and given the arbitrary nature of guideline-based exposure definitions, wide confidence intervals, and the limited number of contributing studies, the relationship cannot be confidently interpreted. Accordingly, the overall certainty of evidence was very low due to these methodological constraints (Table 2). Overall, cross-sectional studies reported mixed and often discordant findings, reflecting their inherent limitations and significant heterogeneity across study designs. Reverse causation, residual confounding, and selection and survivorship bias substantially limit the interpretability of these results, and larger longitudinal studies with greater methodological rigor are needed to more accurately estimate the effect of alcohol consumption on the prevalence of neuropathy/NP.

4.4. Limitations

Overall, this review was limited by substantial methodological heterogeneity across all included studies, given significant variability in neuropathy and NP outcome assessments, underlying etiologies, and the classification of alcohol exposure, which implicated various binary and categorical groupings. In particular, several exposure definitions did not consistently distinguish between former, current, lifetime, or unspecified alcohol use, further limiting temporal interpretation and increasing the potential for misclassification. This significantly impacted comparability within study designs during downstream pooled analyses and limited generalizability to a broader clinical context. Alcohol use was measured exclusively by self-report, without objective biological or physiological validation, increasing susceptibility to misclassification and information bias. Given the considerable physical, cognitive, and psychosocial burden associated with alcohol dependence, significant attrition bias was likewise evident. Additionally, in several studies, alcohol consumption was treated as a secondary variable rather than the primary exposure of interest, with limited adjustment for other lifestyle factors such as diet (which may directly impact compressive neuropathies), thereby limiting the ability to accurately estimate its independent effects on neuropathic outcomes. Likewise, although studies enrolling alcohol-dependent populations or individuals with alcohol-related neuropathy were interpreted within the context of their underlying study populations and exposure definitions, their inclusion may have also obscured the independent effect of alcohol as a risk factor. Reverse causation and protopathic bias represented additional key limitations, both within the included studies and this review itself, as individuals with more severe disease may reduce or cease alcohol consumption prior to or during study participation, potentially biasing effect estimates and obscuring the true association. Lastly, several pooled estimates were derived from a limited number of studies or restricted subsets of data, reducing the precision and stability of effect estimates. Given that the included studies were observational in nature, the overall certainty of evidence was inherently limited, with risk of bias and other methodological constraints further reducing its consistency, precision, and directness. However, despite these limitations, the pooled analyses demonstrated a statistically significant positive association between alcohol exposure and neuropathy/NP incidence and severity.

5. Conclusions

This systematic review identified a broad body of the literature examining the association between alcohol exposure and neuropathy/NP incidence, prevalence, and severity across a range of underlying etiologies. The reported data and pooled effect estimates suggest that alcohol consumption and dependence are associated with increased odds of incident neuropathy and NP overall. These associations were most consistently observed in common non-infectious conditions, including diabetes, cancer, and alcohol use disorders, while a notable gap remains in understanding their impact within infectious etiologies such as leprosy, highlighting the need for further research in underrepresented infectious disease contexts where excessive alcohol consumption may exacerbate underlying disease states. Overall, alcohol consumption and dependence appear to directly influence neuropathic outcomes, while cessation may represent a low-risk, low-cost, and low-tech adjunctive therapeutic strategy. Although pooled estimates were directionally consistent with the broader literature, indicating increased incidence and severity of neuropathy/NP with greater alcohol consumption, the strength of these associations is limited by substantial methodological constraints.

Future Directions

Future research should prioritize larger, well-designed studies, including comprehensive abstinence-based and/or harm reduction-based interventional trials, to strengthen the current evidence base. Standardized and well-defined alcohol exposure classifications, including clear differentiation between current, former, and lifetime use, alongside consistent neuropathy outcome measures and disease-specific analyses, will be critical to improving comparability across studies. Additionally, longitudinal designs with improved temporal resolution are needed to better address reverse causation and clarify the independent effects of alcohol on neuropathy and NP. Ultimately, such efforts will be essential to inform targeted, evidence-based strategies for reducing the burden of neuropathy and NP across diverse clinical populations.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/brainsci16060551/s1, Table S1: PRISMA Checklist. Reference [88] is cited in the supplementary materials.

Author Contributions

Conceptualization, M.K. and A.K.B.; methodology, M.K. and A.K.B.; software, M.K. and A.K.B.; validation, M.K. and A.K.B.; formal analysis, M.K. and A.K.B.; investigation, E.J.B., A.R.-J., R.D. and C.M.; resources, M.K. and A.K.B.; data curation, E.J.B., A.R.-J., R.D. and C.M.; writing—original draft preparation, M.K.; writing—review and editing, M.K. and A.K.B.; visualization, M.K.; supervision, A.K.B.; project administration, M.K. and A.K.B.; funding acquisition, M.K. and A.K.B. All authors have read and agreed to the published version of the manuscript.

Funding

Dr. Boggild is supported as a Clinician Scientist by the Department of Medicine at the University Health Network. M. Klowak is supported by the Queen Elizabeth II Graduate Scholarship in Science and Technology and Open Award from the Institute of Medical Science at the University of Toronto.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors on request.

Acknowledgments

The authors would like to thank the following Boggild Lab team members for contributions to title and abstract screening in this systematic review: Asal Adawi, Charles Adeyinka, Zain Ahmad, Layla Ahmed, Eunice Aluko, Johnnie Ategika, Yashvi Bharwada, Shveta Bhasker, Afia Birago, Shaleesa Clarke, Dileesha Fernando, Anacoana Hernandez, Nessika Karsenti, Rachel Lau, Raesham Mahmood, Milca Meconnen, Mariyam Mohammed, Adhiyat Najam, Arghavan Omidi, Camille Renee, Mahmud Sam, Bethel Samson, Kalsoom Shahzad.

Conflicts of Interest

The authors declare no conflicts of interest. Dr. Boggild oversees the Tropical Disease Fund for Excellence at the University Health Network Foundation, which has received a generous unrestricted educational grant from Seegene Canada. Neither Seegene nor UHN contributed to the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
AUDAlcohol Use Disorder
BMIBody Mass Index
CIDPChronic Inflammatory Demyelinating Polyradiculoneuropathy
CRPSComplex Regional Pain Syndrome
DSNDistal Symmetric Neuropathy
NPNeuropathic Pain
PNPeripheral Neuropathy
PoNPolyneuropathy
SFNSmall Fiber Neuropathy

References

  1. Klowak, M.; Boggild, A.K. A Review of Nutrition in Neuropathic Pain of Leprosy. Ther. Adv. Infect. Dis. 2022, 9, 20499361221102663. [Google Scholar] [CrossRef] [PubMed]
  2. Julian, T.; Glascow, N.; Syeed, R.; Zis, P. Alcohol-Related Peripheral Neuropathy: A Systematic Review and Meta-Analysis. J. Neurol. 2019, 266, 2907–2919. [Google Scholar] [CrossRef]
  3. Mellion, M.; Gilchrist, J.M.; De La Monte, S. Alcohol-Related Peripheral Neuropathy: Nutritional, Toxic, or Both? Muscle Nerve 2011, 43, 309–316. [Google Scholar] [CrossRef]
  4. Sacks, J.J.; Gonzales, K.R.; Bouchery, E.E.; Tomedi, L.E.; Brewer, R.D. 2010 National and State Costs of Excessive Alcohol Consumption. Am. J. Prev. Med. 2015, 49, e73–e79. [Google Scholar] [CrossRef] [PubMed]
  5. Chopra, K.; Tiwari, V. Alcoholic Neuropathy: Possible Mechanisms and Future Treatment Possibilities. Br. J. Clin. Pharmacol. 2012, 73, 348–362. [Google Scholar] [CrossRef]
  6. Paul, P.; Campbell, G.; Zekeridou, A.; Mauermann, M.; Naddaf, E. Diagnosing Peripheral Neuropathy in Patients With Alcohol Use Disorder. Mayo Clin. Proc. 2024, 99, 1299–1305. [Google Scholar] [CrossRef]
  7. Zhang, B.; Xie, T.T.; Ma, Q.; Jiang, Y.P.; Wang, Y.M. Research Progress of Exosome—Derived microRNA in Alcohol Use Disorders: A Critical Review. Addict. Biol. 2026, 31, e70124. [Google Scholar] [CrossRef] [PubMed]
  8. Gallelli, L.; Cione, E.; Caroleo, M.C.; Carotenuto, M.; Lagana, P.; Siniscalchi, A.; Guidetti, V. microRNAs to Monitor Pain-Migraine and Drug Treatment. MicroRNA 2017, 6, 152–156. [Google Scholar] [CrossRef]
  9. Klowak, M.; Lau, R.; Mohammed, M.N.; Birago, A.; Samson, B.; Ahmed, L.; Renee, C.; Meconnen, M.; Sam, M.; Boggild, A.K. A Systematic Review of Dietary Lifestyle Interventions for Neuropathic Pain. J. Clin. Med. 2024, 13, 6766. [Google Scholar] [CrossRef]
  10. Dong, Y.; Buczynski, M.W.; Gregus, A.M. Alcohol Use Disorder-Associated Pain: Clinical and Preclinical Evidence. Alcohol 2025, 129, 14–40. [Google Scholar] [CrossRef]
  11. Klowak, M.; Lau, R.; Mohammed, M.; Birago, A.; Samson, B.; Ahmed, L.; Renee, C.; Meconnen, M.; Bado, E.; Reid-John, A.; et al. A Systematic Review of Lifestyle Interventions for Neuropathy and Neuropathic Pain: Smoking Cessation. NeuroSci 2025, 6, 74. [Google Scholar] [CrossRef] [PubMed]
  12. Adler, A.I.; Boyko, E.J.; Ahroni, J.H.; Stensel, V.; Forsberg, R.C.; Smith, D.G. Risk Factors for Diabetic Peripheral Sensory Neuropathy Results of the Seattle Prospective Diabetic Foot Study. Diabetes Care 1997, 20, 1162–1167. [Google Scholar] [CrossRef]
  13. Braffett, B.H.; Gubitosi-Klug, R.A.; Albers, J.W.; Feldman, E.L.; Martin, C.L.; White, N.H.; Orchard, T.J.; Lopes-Virella, M.; Lachin, J.M.; Pop-Busui, R. Risk Factors for Diabetic Peripheral Neuropathy and Cardiovascular Autonomic Neuropathy in the Diabetes Control and Complications Trial/Epidemiology of Diabetes Interventions and Complications (DCCT/EDIC) Study. Diabetes 2020, 69, 1000–1010. [Google Scholar] [CrossRef]
  14. Christensen, D.H.; Knudsen, S.T.; Gylfadottir, S.S.; Christensen, L.B.; Nielsen, J.S.; Beck-Nielsen, H.; Sørensen, H.T.; Andersen, H.; Callaghan, B.C.; Feldman, E.L.; et al. Metabolic Factors, Lifestyle Habits, and Possible Polyneuropathy in Early Type 2 Diabetes: A Nationwide Study of 5249 Patients in the Danish Centre for Strategic Research in Type 2 Diabetes (Dd2) Cohort. Diabetes Care 2020, 43, 1266–1275. [Google Scholar] [CrossRef] [PubMed]
  15. Elgendy, R.; Deschênes, S.S.; Burns, R.J.; Levy, M.; Schmitz, N. Alcohol Consumption, Depressive Symptoms, and the Incidence of Diabetes-Related Complications. J. Diabetes 2019, 11, 14–22. [Google Scholar] [CrossRef] [PubMed]
  16. Ellis, R.J.; Diaz, M.; Sacktor, N.; Marra, C.; Collier, A.C.; Clifford, D.B.; Calcutt, N.; Fields, J.A.; Heaton, R.K.; Letendre, S.L.; et al. Predictors of Worsening Neuropathy and Neuropathic Pain after 12 Years in People with HIV. Ann. Clin. Transl. Neurol. 2020, 7, 1166–1173. [Google Scholar] [CrossRef]
  17. Hawley, R.J.; Kurtzke, J.F.; Armbrustmacher, V.W.; Saini, N.; Manz, H. The Course of Alcoholic-Nutritional Peripheral Neuropathy. Acta Neurol. Scand. 1982, 66, 582–589. [Google Scholar]
  18. Hillbom, M.; Wennbergt, A. Prognosis of Alcoholic Peripheral Neuropathy. J. Neurol. Neurosurg. Psychiatry 1984, 47, 699–703. [Google Scholar] [CrossRef]
  19. Iturralde, E.; Slama, N.E.; Balapal, N.; Knox, M.J.; Gilliam, L.K.; Satre, D.D.; Sterling, S.A.; Asyyed, A. Type 2 Diabetes Health Care Outcomes for Patients with Alcohol Use Disorder Starting Addiction Treatment. J. Gen. Intern. Med. 2025, 40, 2934–2943. [Google Scholar] [CrossRef]
  20. Kerns, S.L.; Dinh, P.C.; Monahan, P.O.; Stump, T.; Fung, C.; Sesso, H.D.; Feldman, D.R.; Hamilton, R.J.; Vaughn, D.J.; Huddart, R.; et al. Factors Associated with Longitudinal Progression of the Cumulative Burden of Morbidity and Overall Mortality after Cisplatin-Based Chemotherapy for Testicular Cancer. JNCI J. Natl. Cancer Inst. 2025, 117, 1797–1808. [Google Scholar] [CrossRef]
  21. Khan, M.T.F.; Lewis, D.; Kaelber, D.C.; Winhusen, T.J. Health Outcomes Associated with Patterns of Substance Use Disorders among Patients with Type 2 Diabetes and Hypertension: Electronic Health Record Findings. Prim. Care Diabetes 2023, 17, 43–47. [Google Scholar] [CrossRef]
  22. Kindl, G.; Teichmüller, K.; Escolano-Lozano, F.; Birklein, F.; Rittner, H.L. Pain, Disability, and Lifestyle: Patients with Complex Regional Pain Syndrome Compared to Chronic Musculoskeletal Pain—A Retrospective Analysis. Eur. J. Pain UK 2022, 26, 719–728. [Google Scholar] [CrossRef]
  23. Kuguyo, O.; Matimba, A.; Madziyire, M.G.; Magwali, T.; Dandara, C.; Nhachi, C.F.; Tsikai, N. Prevalence and Predictors for Cisplatin-Induced Toxicities in Zimbabwean Women with Cervical Cancer. Future Oncol. 2024, 20, 1909–1924. [Google Scholar] [CrossRef]
  24. Lehtinen, J.M.; Niskanen, L.; Hyv6nen, K.; Siitonen, O.; Uusitupa, M. Nerve Function and Its Determinants in Patients with Newly-Diagnosed Type 2 (Non-Insulin-Dependent) Diabetes Mellitus and in Control Subjects—A 5-Year Follow-Up. Diabetologia 1993, 36, 68–72. [Google Scholar] [CrossRef]
  25. Sreeram, K.; Seaton, R.; Greenwald, M.K.; Kamgar, M.; Assad, H.; Baird, T.; Schwartz, A.G.; Ruterbusch, J.; Simon, M.S. Chemotherapy-Induced Peripheral Neuropathy in the Detroit Research on Cancer Survivors (ROCS) Cohort. Cancer Causes Control 2023, 34, 459–468. [Google Scholar] [CrossRef] [PubMed]
  26. Xu, H.; Li, H.; Fan, Y.; Zhang, S.; Wang, Y.; Wang, Y.; Zhou, L.; Zhang, J. Trajectory of Chemotherapy-Induced Peripheral Neuropathy and Its Predictive Factors in Breast Cancer Patients: A Prospective Longitudinal Study. Clin. Breast Cancer 2026, 26, 306–314. [Google Scholar] [CrossRef] [PubMed]
  27. Agelink, M.W.; Malessa, R.; Weisser, U.; Lemmer, W.; Zeit, T.; Majewski, T.; Klieser, E. Alcoholism, Peripheral Neuropathy (PNP) and Cardiovascular Autonomic Neuropathy (CAN). J. Neurol. Sci. 1998, 161, 135–142. [Google Scholar] [CrossRef]
  28. Doneddu, P.E.; Bianchi, E.; Cocito, D.; Manganelli, F.; Fazio, R.; Filosto, M.; Mazzeo, A.; Cosentino, G.; Cortese, A.; Jann, S.; et al. Risk Factors for Chronic Inflammatory Demyelinating Polyradiculoneuropathy (CIDP): Antecedent Events, Lifestyle and Dietary Habits. Data from the Italian CIDP Database. Eur. J. Neurol. 2020, 27, 136–143. [Google Scholar] [CrossRef]
  29. Fouchard, M.; Brenaut, E.; Genestet, S.; Ficheux, A.S.; Marcorelles, P.; Misery, L. Observational Case-Control Study of Small-Fiber Neuropathies, with Regards on Smoking and Vitamin D Deficiency and Other Possible Causes. Front. Med. 2023, 9, 1051967. [Google Scholar] [CrossRef]
  30. Franklin, G.M.; Shetterly, S.M.; Cohen, J.A.; Baxter, J.; Hamman, R.F. Risk Factors for Distal Symmetric Neuropathy in the San Luis Valley Diabetes Study. Diabetes Care 1994, 17, 1172–1177. [Google Scholar] [CrossRef]
  31. Frost, P.; Johnsen, B.; Fuglsang-Frederiksen, A.; Svendsen, S.W. Lifestyle Risk Factors for Ulnar Neuropathy and Ulnar Neuropathy-like Symptoms. Muscle Nerve 2013, 48, 507–515. [Google Scholar] [CrossRef]
  32. Gebabo, T.F.; Zewdie, T.H.; Shagaro, S.S.; Haile, F. Determinants of Peripheral Neuropathy among Diabetic Patients under Follow-Up in Chronic Care Clinics of Public Hospitals at Gamo and Gofa Zones, Southern Ethiopia. PLoS ONE 2021, 16, e0246722. [Google Scholar] [CrossRef] [PubMed]
  33. Koike, H.; Mori, K.; Misu, K.; Hattori, N.; Ito, H.; Hirayama, M.; Sobue, G. Painful Alcoholic Polyneuropathy with Predominant Small-Fiber Loss and Normal Thiamine Status. Neurology 2001, 56, 1727–1732. [Google Scholar] [CrossRef] [PubMed]
  34. Mitchell, B.D.; Hawthorne, V.M.; Vinik, A.I. Short Reports Cigarette Smoking and Neuropathy in Diabetic Patients. Diabetes Care 1990, 13, 434–437. [Google Scholar] [CrossRef]
  35. Mondelli, M.; Mattioli, S.; Vinciguerra, C.; Ciaramitaro, P.; Aretini, A.; Greco, G.; Sicurelli, F.; Giorgi, S.; Curti, S. Comorbidities, Anthropometric, Demographic, and Lifestyle Risk Factors for Ulnar Neuropathy at the Elbow: A Case Control Study. J. Peripher. Nerv. Syst. 2020, 25, 401–412. [Google Scholar] [CrossRef]
  36. Pessione, F.; Louis Gerchstein, J.; Rueff, B. Parental History of Alcoholism: A Risk Factor for Alcohol-Related Peripheral Neuropathies. Alcohol Alcohol. 1995, 30, 749–754. [Google Scholar] [CrossRef]
  37. Richardson, J.K.; Ho, S.; Wolf, J.; Spiegelberg, T. The Nature of the Relationship between Smoking and Ulnar Neuropathy at the Elbow. Am. J. Phys. Med. Rehabil. 2016, 88, 711–718. [Google Scholar] [CrossRef]
  38. Walsh, J.C.; Mcleod, J.G. Alcoholic Neuropathy An Electrophysiological and Histological Study. J. Neurol. Sci. 1970, 10, 457–469. [Google Scholar] [CrossRef]
  39. Alessi, S.M.; Foster, N.C.; Rash, C.J.; Van Name, M.A.; Tamborlane, W.V.; Cengiz, E.; Polsky, S.; Wagner, J. Alcohol Use and Clinical Outcomes in Adults in the Type 1 Diabetes Exchange. Can. J. Diabetes 2020, 44, 501–506. [Google Scholar] [CrossRef]
  40. Ammendola, A.; Gemini, D.; Iannaccone, S.; Argenzio, F.; Ciccone, G.; Ammendola, E.; Serio, L.; Ugolini, G.; Bravaccio, F. Gender and Peripheral Neuropathy in Chronic Alcoholism: A Clinical–Electroneurographic Study. Alcohol Alcohol. 2000, 35, 368–371. [Google Scholar] [CrossRef] [PubMed]
  41. Ammendola, A.; Tata, M.R.; Aurilio, C.; Ciccone, G.; Gemini, D.; Ammendola, E.; Ugolini, G.; Argenzio, F. Peripheral Neuropathy in Chronic Alcoholism: A Retrospective Cross-Sectional Study in 76 Subjects. Alcohol Alcohol. 2001, 36, 271–275. [Google Scholar] [CrossRef]
  42. Asai, A.; Suzuki, F.; Tsujiguchi, H.; Hara, A.; Miyagi, S.; Kannon, T.; Suzuki, K.; Nakamura, M.; Shimizu, Y.; Nguyen, T.T.T.; et al. Relationship between Fatty Acid Intake and Chronic Neck/Shoulder/Upper Limb Pain without Elevated CRP in a Japanese Population: A Cross-Sectional Analysis of the Shika Study. J. Nutr. Sci. 2022, 11, e38. [Google Scholar] [CrossRef]
  43. Beulens, J.W.J.; Kruidhof, J.S.; Grobbee, D.E.; Chaturvedi, N.; Fuller, J.H.; Soedamah-Muthu, S.S. Alcohol Consumption and Risk of Microvascular Complications in Type 1 Diabetes Patients: The EURODIAB Prospective Complications Study. Diabetologia 2008, 51, 1631–1638. [Google Scholar] [CrossRef]
  44. Blackstock, E.; Rushworth, G.; Gath, D. Electrophysiological Studies in Alcoholism. J. Neurol. Neurosurg. Psychiatry 1972, 35, 326–334. [Google Scholar] [CrossRef]
  45. Callaghan, B.C.; Reynolds, E.; Banerjee, M.; Chant, E.; Villegas-Umana, E.; Feldman, E.L. Central Obesity Is Associated with Neuropathy in the Severely Obese. Mayo Clin. Proc. 2020, 95, 1342–1353. [Google Scholar] [CrossRef]
  46. Chang, W.; Li, X.; Ma, Y.; Bai, T.; Jia, L. Relationship Between Chronic Inflammatory Indicators and Diabetic Peripheral Neuropathy in Hospitalized Elderly Patients with Type 2 Diabetes. Diabetes Metab. Syndr. Obes. 2025, 18, 3075–3088. [Google Scholar] [CrossRef]
  47. Chaware, N.; Borle, A.; Reddy, A.; Shiddapur, G.S.; Dhadwad, J.S.; Vikhe, V. Study of Clinical Profile of Peripheral Neuropathy in Chronic Alcoholics. Pravara Med. Rev. 2022, 14, 35–39. [Google Scholar] [CrossRef]
  48. Ching, S.M.; Lee, K.W.; Yusof Khan, A.H.K.; Devaraj, N.K.; Cheong, A.T.; Yap, S.F.; Hoo, F.K.; Wan Sulaiman, W.A.; Loh, W.C.; Chong, S.H.; et al. Prevalence and Factors Associated with Peripheral Neuropathy in a Setting of Retail Pharmacies in Malaysia–A Cross-Sectional Study. PLoS ONE 2024, 19, e0307093. [Google Scholar] [CrossRef]
  49. Chukwubuzo, O.T.; Chibuike, O.P.; Philip, O.C.; Sunday, E.M.; Ekpunobi, C.P.; Sochima, E.E.; Obumneme, O.A.; Gerald, U.; Diuto Ifeoma, O.; Ugwu, A.R. Prevalence and Associations of Neuropathic Pain Among Subjects with Diabetes Mellitus in the Enugu Diabetic Peripheral Neuropathy (Edipen) Study. J. Pharm. Negat. Results 2022, 13, 10104–10117. [Google Scholar] [CrossRef]
  50. Claus, D.; Eggers, R.; Engelhardt, A.; Neundörfer, B.; Warecka, K. Ethanol and Polyneuropathy. Acta Neurol. Scand. 2009, 72, 312–316. [Google Scholar] [CrossRef]
  51. Corrêa, L.A.; Bittencourt, J.V.; Mathieson, S.; Nogueira, L.A.C. Pain-Related Interference and Pain-Related Psychosocial Factors of Three Different Subgroups of Patients with Chronic Low Back Pain. Musculoskelet. Sci. Pract. 2023, 63, 102718. [Google Scholar] [CrossRef]
  52. D’Amour, M.L.; Bruneau, J.; Butterworth, R.F. Abnormalities of Peripheral Nerve Conduction in Relation to Thiamine Status in Alcoholic Patients. Can. J. Neurol. Sci. J. Can. Sci. Neurol. 1991, 18, 126–128. [Google Scholar] [CrossRef][Green Version]
  53. Estruch, R.; Nicolas, J.M.; Villegas, E.; Junque, A.; Urbano-Marquez, A. Relationship Between Ethanol-Related Diseases and Nutritional Status in Chronically Alcoholic Men. Alcohol Alcohol. 1993, 28, 543–550. [Google Scholar] [CrossRef]
  54. Fernandez-Soli, J.; Sacanella, E.; Estruch, R.; Nicolk, J.-M.; Grau, J.-M.; Urbano-Marquez, A. Significance of Type II Fiber Atrophy in Chronic Alcoholic Myopathy. J. Neurol. Sci. 1995, 130, 69–76. [Google Scholar] [CrossRef]
  55. Gierthmühlen, J.; Attal, N.; Baskozos, G.; Bennedsgaard, K.; Bennett, D.L.; Bouhassira, D.; Crombez, G.; Finnerup, N.B.; Granovsky, Y.; Jensen, T.S.; et al. What Is Associated with Painful Polyneuropathy? A Cross-Sectional Analysis of Symptoms and Signs in Patients with Painful and Painless Polyneuropathy. Pain 2024, 165, 2888–2899. [Google Scholar] [CrossRef] [PubMed]
  56. Gylfadottir, S.S.; Christensen, D.H.; Nicolaisen, S.K.; Andersen, H.; Callaghan, B.C.; Itani, M.; Khan, K.S.; Kristensen, A.G.; Nielsen, J.S.; Sindrup, S.H.; et al. Diabetic Polyneuropathy and Pain, Prevalence, and Patient Characteristics: A Cross-Sectional Questionnaire Study of 5514 Patients with Recently Diagnosed Type 2 Diabetes. Pain 2020, 161, 574–583. [Google Scholar] [CrossRef] [PubMed]
  57. Hicks, C.W.; Wang, D.; Lin, F.R.; Reed, N.; Windham, B.G.; Selvin, E. Peripheral Neuropathy and Vision and Hearing Impairment in US Adults With and Without Diabetes. Am. J. Epidemiol. 2023, 192, 237–245. [Google Scholar] [CrossRef]
  58. Ireri, R.; Kikuvi, G.; Mambo, S.; Cheriro, B.C.R. Prevalence of Microvascular Complications and Associated Risk Factors among Diabetes Mellitus Patients Attending Nyeri County Referral Hospital, Kenya: A Cross-Sectional Study. Open J. Epidemiol. 2024, 14, 444–458. [Google Scholar] [CrossRef]
  59. Jeyam, A.; McGurnaghan, S.J.; Blackbourn, L.A.K.; McKnight, J.M.; Green, F.; Collier, A.; McKeigue, P.M.; Colhoun, H.M.; Chalmers, J.; Fischbacher, C.; et al. Diabetic Neuropathy Is a Substantial Burden in People with Type 1 Diabetes and Is Strongly Associated with Socioeconomic Disadvantage: A Population-Representative Study from Scotland. Diabetes Care 2020, 43, 734–742. [Google Scholar] [CrossRef]
  60. Li, C.; Wang, W.; Ji, Q.; Ran, X.; Kuang, H.; Yu, X.; Fang, H.; Yang, J.; Liu, J.; Xue, Y.; et al. Prevalence of Painful Diabetic Peripheral Neuropathy in Type 2 Diabetes Mellitus and Diabetic Peripheral Neuropathy: A Nationwide Cross-Sectional Study in Mainland China. Diabetes Res. Clin. Pract. 2023, 198, 110602. [Google Scholar] [CrossRef]
  61. Mawdsley, C.; Mayer, R.F. Nerve Conduction in Alcoholic Polyneuropathy. Brain 1965, 88, 335–356. [Google Scholar] [CrossRef]
  62. Mcculloch, D.K.; Campbell, I.W.; Prescott, R.J.; Clarke, B.F. Effect of Alcohol Intake on Symptomatic Peripheral Neuropathy in Diabetic Men. Diabetes Care 1980, 3, 245–247. [Google Scholar] [CrossRef]
  63. Melgaard, B.; Saelan, H.; Hedegaard, L. Symptoms and Signs of Polyneuropathy and Their Relation to Alcohol Intake in a Normal Male Population. Acta Neurol. Scand. 1986, 73, 458–460. [Google Scholar] [CrossRef]
  64. Mellion, M.L.; Silbermann, E.; Gilchrist, J.M.; Machan, J.T.; Leggio, L.; de la Monte, S. Small-Fiber Degeneration in Alcohol-Related Peripheral Neuropathy. Alcohol. Clin. Exp. Res. 2014, 38, 1965–1972. [Google Scholar] [CrossRef]
  65. Mick, G.; Serpell, M.; Baron, R.; Mayoral, V.; Hans, G.; Mendez, I.; Artime, E.; Qizilbash, N.; Sohns, M. Localised Neuropathic Pain in the Primary Care Setting: A Cross-Sectional Study of Prevalence, Clinical Characteristics, Treatment Patterns, Quality of Life and Sleep Performance. Curr. Med. Res. Opin. 2021, 37, 293–302. [Google Scholar] [CrossRef]
  66. Mills, K.R.; Ward, K.; Martin, F.; Peters, T.J. Peripheral Neuropathy and Myopathy in Chronic Alcoholism. Alcohol Alcohol. 1986, 21, 357–362. [Google Scholar] [CrossRef]
  67. Monforte, R.; Estruch, R.; Valls-Sole, J.; Nicolas, J.; Villalta, J.; Urbano-Marquez, A. Autonomic and Peripheral Neuropathies in Patients with Chronic Alcoholism. Arch. Neurol. 1995, 52, 45–51. [Google Scholar] [CrossRef]
  68. Nagakura, Y.; Hayashi, M.; Kajioka, S. Analysis of Japanese Nationwide Health Datasets: Association between Lifestyle Habits and Prevalence of Neuropathic Pain and Fibromyalgia with Reference to Dementia-Related Diseases and Parkinson’s Disease. Scand. J. Pain 2023, 23, 662–669. [Google Scholar] [CrossRef]
  69. Nicolosi, C.; Di Leo, R.; Girlanda, P.; Messina, C.; Vita, G. Is There a Relationship between Somatic and Autonomic Neuropathies in Chronic Alcoholics? J. Neurol. Sci. 2005, 228, 15–19. [Google Scholar] [CrossRef]
  70. Nielsen, S.W.; Eckhoff, L.; Ruhlmann, C.H.B.; Herrstedt, J.; Dalton, S.O. The Prevalence, Distribution and Impact of Peripheral Neuropathy among Danish Patients with Cancer—A Population-Based Cross-Sectional Study. Acta Oncol. 2022, 61, 363–370. [Google Scholar] [CrossRef]
  71. Papantoniou, M.; Rentzos, M.; Zampelis, T.; Tzavellas, E.; Paparrigopoulos, T.; Kokotis, P. Alcohol-Related Peripheral Neuropathy: Clinico-Neurophysiological Characteristics and Diagnostic Utility of the Neuropathy Symptoms Score and the Neuropathy Impairment Score. Alcohol 2024, 117, 65–71. [Google Scholar] [CrossRef]
  72. Révész, D.; Bonhof, C.S.; Bours, M.J.L.; Weijenberg, M.P.; Vreugdenhil, G.; Van De Poll-Franse, L.V.; Mols, F. Sociodemographic, Clinical, Lifestyle, and Psychological Correlates of Peripheral Neuropathy among 2- to 12-Year Colorectal Cancer Survivors. Oncol. Res. Treat. 2022, 45, 480–493. [Google Scholar] [CrossRef]
  73. Sahito, D.A.; Rahu, S.A.; Samad, A.; Hayee, P.A.; Zaman Shaikh, M.; Naseem, S. Assessment of Prevalence and the Risk Factors of Diabetic Peripheral Neuropathy at Primary Health Care Level at Nawab Shah. Pak. J. Med. Health Sci. 2022, 16, 330–332. [Google Scholar] [CrossRef]
  74. Shetty, A.A.; Shetty, B.A.; Shetty, S.B.; Bhagyalakshmi, K.; Nayanatara, A.; Shetty, A.B. A Longitudinal Study on Association of Alcohol-Induced Liver Dysfunction with Neurological Consequences and Clinical Implications. Clin. Ter. 2025, 176, 567–572. [Google Scholar] [CrossRef]
  75. Srivastava, S.P.; Sinha, A.P.; Sharma, K.K.; Malik, P.S. Severity, Risk Factors and Quality of Life of Patients Associated with Chemotherapy-Induced Peripheral Neuropathy. Clin. Nurs. Res. 2022, 31, 1080–1090. [Google Scholar] [CrossRef]
  76. Trendowski, M.R.; Lusk, C.M.; Ruterbusch, J.J.; Seaton, R.; Simon, M.S.; Greenwald, M.K.; Harper, F.W.K.; Beebe-Dimmer, J.L.; Schwartz, A.G. Chemotherapy-Induced Peripheral Neuropathy in African American Cancer Survivors: Risk Factors and Quality of Life Outcomes. Cancer Med. 2021, 10, 8151–8161. [Google Scholar] [CrossRef] [PubMed]
  77. van der Velde, J.H.P.M.; Koster, A.; Strotmeyer, E.S.; Mess, W.H.; Hilkman, D.; Reulen, J.P.H.; Stehouwer, C.D.A.; Henry, R.M.A.; Schram, M.T.; van der Kallen, C.J.H.; et al. Cardiometabolic Risk Factors as Determinants of Peripheral Nerve Function: The Maastricht Study. Diabetologia 2020, 63, 1648–1658. [Google Scholar] [CrossRef] [PubMed]
  78. Villalta, J.; Estruch, R.; Antunez, E.; Valls, J.; Urbano-Marquez, A. Vagal Neuropathy in Chronic Alcoholics: Relation to Ethanol Consumption. Alcohol Alcohol. 1989, 24, 421–428. [Google Scholar] [CrossRef]
  79. Vittadini, G.; Buonocore, M.; Colli, G.; Terzi, M.; Fonte, R.; Biscaldi, G. Alcoholic Polyneuropathy: A Clinical and Epidemiological Study. Alcohol Alcohol. 2001, 36, 393–400. [Google Scholar] [CrossRef]
  80. Wang, W.; Ji, Q.; Ran, X.; Li, C.; Kuang, H.; Yu, X.; Fang, H.; Yang, J.; Liu, J.; Xue, Y.; et al. Prevalence and Risk Factors of Diabetic Peripheral Neuropathy: A Population-Based Cross-Sectional Study in China. Diabetes Metab. Res. Rev. 2023, 39, e3702. [Google Scholar] [CrossRef] [PubMed]
  81. Wetterling, T.; Veltrup, C.; Driessen, M.; John, U. Drinking Pattern and Alcohol-Related Medical Disorders. Alcohol Alcohol. 1999, 34, 330–336. [Google Scholar] [CrossRef]
  82. Wilson, I.; Thompson, T. Association between Medically Assisted Detoxification and Neuropathic Pain. In Nursing Standard; The University of Greenwich: London, UK, 2021. [Google Scholar]
  83. Wu, Y.H.A.; He, J.H.; McDermott, K.M.; Wang, D.; Fang, M.; Windham, B.G.; Selvin, E.; Hicks, C.W. Prevalence of Peripheral Neuropathy Among Very Old Adults: Evidence from the Michigan Neuropathy Screening Instrument. J. Am. Geriatr. Soc. 2025, 73, 3530–3538. [Google Scholar] [CrossRef]
  84. Yokoyama, H.; Tsuji, T.; Hayashi, S.; Kabata, D.; Shintani, A. Factors Associated with Diabetic Polyneuropathy-Related Sensory Symptoms and Signs in Patients with Polyneuropathy: A Cross-Sectional Japanese Study (JDDM 52) Using a Non-Linear Model. J. Diabetes Investig. 2020, 11, 450–457. [Google Scholar] [CrossRef]
  85. Zahr, N.M.; Pohl, K.M.; Pfefferbaum, A.; Sullivan, E.V. Central Nervous System Correlates of “Objective” Neuropathy in Alcohol Use Disorder. Alcohol. Clin. Exp. Res. 2019, 43, 2144–2152. [Google Scholar] [CrossRef]
  86. Zambelis, T.; Karandreas, N.; Tzavellas, E.; Kokotis, P.; Liappas, J. Large and Small Fiber Neuropathy in Chronic Alcohol-Dependent Subjects. J. Peripher. Nerv. Syst. 2005, 10, 375–381. [Google Scholar]
  87. Zambelis, T.; Kanelli, S.; Tzavellas, E.; Paparrigopoulos, T.; Karandreas, N. Ulnar Neuropathy at the Elbow in Chronic Alcohol-Dependent Subjects. J. Clin. Neuromusc. Dis. 2016, 18, 28–33. [Google Scholar]
  88. Page, M.J.; McKenzie, J.E.; Bossuyt, P.M.; Boutron, I.; Hoffmann, T.C.; Mulrow, C.D.; Shamseer, L.; Tetzlaff, J.M.; Akl, E.A.; Brennan, S.E.; et al. The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ 2021, 372, n71. [Google Scholar] [CrossRef]
Brainsci 16 00551 g001
Figure 1. PRISMA flowchart.
Figure 1. PRISMA flowchart.
Brainsci 16 00551 g001
Brainsci 16 00551 g002
Figure 2. Risk of bias assessment for cohort studies. (a) Risk of bias summary by cohort study [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26]; (b) summary of risk of bias items by bias item.
Figure 2. Risk of bias assessment for cohort studies. (a) Risk of bias summary by cohort study [12,13,14,15,16,17,18,19,20,21,22,23,24,25,26]; (b) summary of risk of bias items by bias item.
Brainsci 16 00551 g002
Brainsci 16 00551 g003
Figure 3. Risk of bias assessment for case–control studies. (a) Risk of bias summary by case–control study [27,28,29,30,31,32,33,34,35,36,37,38]; (b) summary of risk of bias items by bias item.
Figure 3. Risk of bias assessment for case–control studies. (a) Risk of bias summary by case–control study [27,28,29,30,31,32,33,34,35,36,37,38]; (b) summary of risk of bias items by bias item.
Brainsci 16 00551 g003
Brainsci 16 00551 g004
Figure 4. Risk of bias assessment for cross-sectional studies. (a) Risk of bias summary by cross-sectional study [39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87]; (b) summary of risk of bias items by bias item.
Figure 4. Risk of bias assessment for cross-sectional studies. (a) Risk of bias summary by cross-sectional study [39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55,56,57,58,59,60,61,62,63,64,65,66,67,68,69,70,71,72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87]; (b) summary of risk of bias items by bias item.
Brainsci 16 00551 g004
Brainsci 16 00551 g005
Figure 5. Forest plot of odds ratios of neuropathic outcome according to alcohol consumption in cohort studies.
Figure 5. Forest plot of odds ratios of neuropathic outcome according to alcohol consumption in cohort studies.
Brainsci 16 00551 g005
Brainsci 16 00551 g006
Figure 6. Forest plot of odds ratios of neuropathic outcome according to alcohol dependence in cohort studies.
Figure 6. Forest plot of odds ratios of neuropathic outcome according to alcohol dependence in cohort studies.
Brainsci 16 00551 g006
Brainsci 16 00551 g007
Figure 7. Forest plot of odds ratios of neuropathic outcome according to alcohol overconsumption as per guidelines in cohort studies [14,24].
Figure 7. Forest plot of odds ratios of neuropathic outcome according to alcohol overconsumption as per guidelines in cohort studies [14,24].
Brainsci 16 00551 g007
Brainsci 16 00551 g008
Figure 8. Forest plot of odds ratios of neuropathic outcome according to alcohol consumption in case–control studies [28,30,32,35].
Figure 8. Forest plot of odds ratios of neuropathic outcome according to alcohol consumption in case–control studies [28,30,32,35].
Brainsci 16 00551 g008
Brainsci 16 00551 g009
Figure 9. Forest plot of odds ratios of neuropathic outcome according to alcohol dependence in case–control studies [29,36].
Figure 9. Forest plot of odds ratios of neuropathic outcome according to alcohol dependence in case–control studies [29,36].
Brainsci 16 00551 g009
Brainsci 16 00551 g010
Figure 10. Forest plot of odds ratios of neuropathic outcome according to alcohol consumption in cross-sectional studies [39,42,43,46,48,51,57,58,59,70,73,84],.
Figure 10. Forest plot of odds ratios of neuropathic outcome according to alcohol consumption in cross-sectional studies [39,42,43,46,48,51,57,58,59,70,73,84],.
Brainsci 16 00551 g010
Brainsci 16 00551 g011
Figure 11. Forest plot of odds ratios of neuropathic outcome according to alcohol dependence in cross-sectional studies [67,80,85].
Figure 11. Forest plot of odds ratios of neuropathic outcome according to alcohol dependence in cross-sectional studies [67,80,85].
Brainsci 16 00551 g011
Brainsci 16 00551 g012
Figure 12. Forest plot of odds ratios of neuropathic outcome according to alcohol overconsumption as per guidelines in cross-sectional studies [56,77].
Figure 12. Forest plot of odds ratios of neuropathic outcome according to alcohol overconsumption as per guidelines in cross-sectional studies [56,77].
Brainsci 16 00551 g012
Table 1. Characteristics of all observational studies of alcohol and neuropathy/NP included in this review.
Table 1. Characteristics of all observational studies of alcohol and neuropathy/NP included in this review.
Author (Year)Study DesignSettingNSex N (F:M)Age (Mean ± SD, (Range))Population/EtiologyLifestyleOutcomes
Adler (1997) [12]Cohort StudyUSWith Ne: 58; Without Ne: 230With Ne: 1:57; Without Ne: 11:219With Ne: 64.0; Without Ne: 61.5DM ± Incident NeAlcohol: CAGE score, history of treatment, current useHigh (4) CAGE alcohol score significantly associated with incident Ne (41.7% vs. 58.3%, p = 0.049; β = 1.94, SE = 0.7281, 6.96 [1.67–28.99], p = 0.008).
Braffett (2020) [13]Cohort StudyUSWith DPN: 455; Without DPN: 931With DPN: 182:273; Without DPN: 475:456^ With DPN: 29 (24, 34); Without DPN 26 (21, 32)T1DM ± DPNOccasional or regular alcohol useAlcohol consumption not significantly associated with DPN (1.14 [0.93–1.41], p > 0.05).
Christensen (2020) [14]Cohort StudyDenmarkOverall: 5249; With DPoN: 938; With DPoN + Pain: 386Overall: 2205:3144^ 65 (57, 72)T2DM ± DPoN ± PainAlcohol: ≤14 (F)/21 (M) units, >14 (F)/21 (M) unitsAlcohol consumption above recommended limit significantly associated with increased pain prevalence (aPR: 1.31 [1.01–1.69].
Elgendy (2019) [15]Cohort StudyCanada1413705:70860 ± 8.4T2DM ± PNAlcohol frequency: Never, ≤1/mo, 2–4/mo, 2–3/wk, ≥4/wk; Number of drinks/dHigh alcohol frequency + depressive symptoms significantly associated with prevalent Ne (1.02 [1.00–1.04], p = 0.04).
Ellis (2020) [16]Cohort StudyUS25454:20043.5 ± 8.01HIV ± DSPoNLifetime Alcohol Abuse: Yes, NoLifetime alcohol abuse not significantly associated with DSPoN (statistics NR).
Hawley (1982) [17]Cohort StudyUS630:6353.3 (29–69)PN due to AlcoholHistory of alcoholismAlcohol abstinence associated with significant electrophysiology improvement in PN (+0.12 m/s/abstinent mo, p < 0.05).
Hillbom (1984) [18]Cohort StudySweden100:1053.1 (38–72)Chronic alcoholism ± PNHistory of alcoholism and seeking rehabilitationAlcohol abstinence associated with improvement in clinical/electrophysiological PN.
Iturralde (2024) [19]Cohort StudyUSOverall: 222,334; AUD+: 1998; AUD−: 220,336Overall: 106,353:115,978; AUD+: 477:1521; AUD−: 105,876:114,457AUD+: 57 ± 11.3; AUD−: 64.3 ± 12.7 T2DM ± AUD ± NeAUD (yes, no)AUD significantly associated with a higher risk of Ne in unadjusted (p < 0.001) and adjusted (p < 0.001) models.
Kerns (2025) [20]Cohort StudyUS1 drink/d: 539; >1 drink/d: 760:61545 (22–79)Testicular cancer survivors ± worsening PSN, or NPHistory of alcohol consumption (1 drink/d, >1 drink/d)Alcohol consumption (>1 drink/d) not significantly associated with PSN (0.75 [0.40–1.44], p = 0.392), or NP (0.76 [0.29–1.98], p = 0.570).
Khan (2023) [21]Cohort StudyUSTUD: 8009; TAUD: 1672; PSUD: 642; TUD Co: 8009; TAUD Co: 1672; PSUD Co: 642TUD: 4660:3349; TAUD: 582:1090; PSUD: 233:409; TUD Co: 4665:3344; TAUD Co: 584:1088; PSUD Co: 234:408TUD: 61.6 ± 12.1; TAUD: 61.52 ± 10.3; PSUD: 57.84 ± 8.3; TUD Co: 61.6 ± 12.1; TAUD Co: 61.42 ± 10; PSUD Co: 57.88 ± 8.1T2DM + Hypertension ± NeTUD: Yes, No; TAUD: Yes, No; PSUD: Yes, NoPSUD associated with significantly higher risk of DN (1.76 [1.33–2.32], p < 0.05) compared to TUD.
Kindl (2021)
[22]		Cohort StudyGermanyWith MSK: 255; With CRPS: 223With MSK: 160:95; With CRPS: 173:50With MSK: 54.6 (20–80); With CRPS: 50.9 (18–77)CRPS or MSK, due to traumaAlcohol Consumption: Yes, No, Daily, Weekly, MonthlyPrevalence of alcohol consumption significant with MSK (58%, p < 0.001), and CRPS (43%, p < 0.001).
Kuguyo (2024) [23]Cohort StudyZimbabwe252252:0(26–90); ^ 50 (43–61)Breast cancer survivors ± sensory loss (cisplatin)History of alcohol consumptionAlcohol consumption not significantly associated with diminished electrophysiology (p > 0.05).
Lehtinen (1993) [24]Cohort StudyFinlandWith ND: 12; Without ND: 101With ND: 9:3; Without ND: 46:55With ND: 57.2 ± 4.7; Without ND: 55.4 ± 10.4DM ± NDAlcohol use (>30 g/wk)Alcohol use not significantly different between ND groups (17% vs. 30%, p > 0.05).
Sreeram (2023) [25]Cohort StudyUSOverall: 1034; With CIPN: 704; Without CIPN: 330Overall: 797:237; With CIPN: 570:134; Without CIPN: 227:103Overall: 57.1 ± 10.9 (27–79); With CIPN: 55.8 ± 10.8 (27–79); Without CIPN: 59.9 ± 10.4 (27–79)Cancer survivors ± CIPNAlcohol use (Past 4 wks): Yes, NoAlcohol use not significantly different between CIPN groups, or associated with CIPN prevalence (51.2% vs. 46.4%, 1.10 [0.81–1.49], p > 0.05).
Xu (2025) [26]Cohort StudyChinaLow-Risk Stable CIPN: 148; Mod-Risk Progressive CIPN: 145; High-Risk Progressive CIPN: 57350:018–44: n = 89; 45–59: n = 179; >60: n = 82Breast cancer survivors ± CIPNHistory of harmful alcohol consumption (yes, no)History of harmful alcohol consumption not significantly different between CIPN groups (1.4% vs. 2.1% vs. 1.8%, x2 = 0.225, p = 0.894).
Agelink (1998) [27]Case–Control StudyGermanyCa: 35; Co: 80Ca: 15:20; Co: 33:47Ca: 42.9 ± 10 (28–74); Co: 41.8 ± 14.7 (27–77)Alcoholism ± PN & CAN vs. healthy coDuration of alcohol dependence (yrs), mean TLDADuration of alcohol dependence was significantly longer (6.1 ± 3.8 vs. 16.2 ± 7.1, p < 0.0005) and mean TLDA was significantly larger (438 ± 342 vs. 1930 ± 1173, p < 0.001) with AUD PN vs. without.
Doneddu (2020) [28]Case–Control StudyItalyCa: 195; Co: 195Ca: 109:86; Co: 109:86NRCIDP due to any etiology and their partnersAlcohol Consumption: Yes, NoAlcohol consumption not significantly associated with CIDP (0.79 [0.50–1.24], p > 0.05).
Fouchard (2023) [29]Case–Control StudyFranceOverall: 323; Ca: 162; Co: 161Overall: 192:131; Ca: 88:74; Co: 104:57Ca: 56 ± 16; Co: 69 ± 13Cutaneous paresthesia ± SFN via IENFD due to any etiologyAlcoholism: Yes, NoAlcohol consumption not significantly different between SFN groups (3.7% vs. 1.2%, p > 0.05).
Franklin (1994) [30]Case–Control StudyUSCa: 77; Co: 200Ca: 29:48; Co: 118:82Ca: 61.7; Co: 58.6NIDDM ± DSNAlcohol use: never, g/wk (<20, >20)Alcohol (g/wk: <20, >20) not significantly associated with DSN (0.71 [0.29–1.72] p = 0.69, 1.03 [0.40–2.62]).
Frost (2013) [31]Case–Control StudyDenmarkCa: 324; Co: 832Ca: 121:203; Co 317:515Ca Smokers: 49 ± 9.7; Ca Non-Smokers: 44 ± 11.5; Co Smokers: 50 ± 9; Co Non-Smokers: 48 ± 9.9Ca: Electroneurographically confirmed UN; Co: Without UNAlcohol: u/wkAlcohol consumption not significantly associated with UN (0.81 [0.44–1.48]).
Gebabo (2021) [32]Case–Control StudyEthiopiaOverall: 528; Ca: 264; Co: 264Ca: 101:163; Co: 105:159Ca: <40: 43; 40–65: 178; 65+: 43; Co: <40: 64; 40–65: 178; 65+: 17T1DM or T2DM ± PNAlcohol Consumption (Ever): Yes, NoAlcohol consumption significantly higher with PN vs. without (5.3% vs. 1.5%, p = 0.024).
Koike (2001) [33]Case–Control StudyJapan180:1847.7 ± 10.5 (31–70)Alcoholism PoN vs. healthy coHistory of heavy alcohol consumption (100 g eth/d for >10 yrs)History of heavy alcohol consumption significantly associated with diminished electrophysiology (p < 0.005).
Mitchell (1990) [34]Case–Control StudyUSIDDM: Ca: 54, Co: 56; NIDDM: Ca: 39, Co: 65IDDM: Ca: 31:23, Co: 35:21; NIDDM: Ca: 25:14, Co: 44:21IDDM: Ca: 36.1, Co: 32.7; NIDDM: 59.4: 39, Co: 57.7DM ± NeAlcohol: median drink-yrsMedian alcohol consumption not significantly associated with Ne in IDDM (996 vs. 485). or NIDDM (0 vs. 14).
Mondelli (2020) [35]Case–Control StudyItalyCa: 220; Co: 460Ca: 84:136; Co: 242:218Ca: 51.7 ± 11.8; Co: 47.8 ± 12.4Ca: UNE; Co: Upper limb complaintsAlcohol: u/wk or dAlcohol consumption not significantly different between UNE groups (p = 0.463).
Pessione (1995) [36]Case–Control StudyFranceCa: 32; Co: 58Ca: 6:26; Co: 22:36Ca: 49 ± 10.1; Co: 46.8 ± 9.6Alcoholism ± PNAlcohol: parental history of alcoholism, alcohol dependence, weekly alcohol consumption (drinks)Alcohol-related risk factors all significantly higher in those with PN vs. without in univariate (p < 0.01); and multivariate p < 0.05) analyses.
Richardson (2016) [37]Case–Control StudyUSCa: 50; Co: 50Ca: 18:32; Co: 34:16Ca: 48.4 ± 12.8; Co: 39.2 ± 12Ca: UNE+; Co: UNE-Alcohol: Eth/wk (ounces)Eth/wk did not significantly differ between UNE groups (1.2 ± 1.9 vs. 1.2 ± 2.2, p = 0.993).
Walsh (1970) [38]Case–Control StudyAustraliaCa: 11; Co: 201:10Ca: 58 (41–73); Co: 54 (38–73)PN due to alcoholismHistory of PN due to alcoholism: Yes, NoHistory of heavy alcohol consumption associated with diminished electrophysiology (p < 0.01), and fiber densities (3.39 ± 0.86 vs. 5.78 ± 0.90, p < 0.001).
Alessi (2020) [39]Cross-Sectional StudyUSOverall: 934; Never Drinker: 103; Former Drinker: 89; Nonbinge Drinker: 567; Binge Drinker: 174Overall: 569:365; Never Drinker: 61:42; Former Drinker: 51:38; Nonbinge Drinker: 373:194; Binge Drinker: 84:90Overall: 38.3 ± 15.8; Never Drinker: 31.8 ± 16.8; Former Drinker: 44.1 ± 16.1; Nonbinge Drinker: 39.8 ± 15.8; Binge Drinker: 34 ± 13T1DM ± PNAlcohol Consumption: Never, Former, Current (Nonbinge), Current (Binge)Ne significantly lower in never vs. former alcohol consumption (11% vs. 35%, p = 0.006).
Ammendola (2000) [40]Cross-Sectional with Nested Case–ControlItaly6218:4443.3 (28–69)Chronic alcoholism (>100 g/d for >2 yrs) ± PNMean alcohol-related disease duration; Mean TLDEDiminished electrophysiology significantly associated with AUD (p < 0.01), longer disease duration (p < 0.01), and higher TLDE (p < 0.05).
Ammendola (2001) [41]Cross-Sectional StudyItalyOverall: 76; With Ne: 51; Without Ne: 25Overall: 21:55; With Ne: 14:37; Without Ne: 7:18Overall: 24–69; With Ne: 45.3 ± 9.4; Without Ne: 39.1 ± 7.7Chronic alcoholism ± PNFamily history of alcoholism (Yes, No); duration of alcoholism; TLDEProlonged alcohol-related disease duration (16.2 ± 9.4 vs. 11.1 ± 8.2, p < 0.05), high TLDE (27.9 vs. 14.8 ± 15.9, p < 0.05), and diminished electrophysiology (p < 0.01) significantly associated with Ne.
Asai (2022) [42]Cross-Sectional StudyJapanOverall: 817; With CP: 35; Without CP: 782Overall: 431:386; With CP: 24:11; Without CP: 407:375With CP: 63.91 [60.11–67.72]; Without CP: 63.75 [63.02–67.72]Chronic neck/shoulder/upper limb pain due to any etiologyCurrent drinker: Yes, NoAlcohol consumption not significantly different between CP groups (42.86% vs. 47.19%, p > 0.05).
Beulens (2008) [43]Cross-Sectional StudyEurope1857893:964(15–60)T1DM ± NeAlcohol consumption (g/wk)Moderate alcohol consumption (30–70 g/wk)/frequency (5–7 d/wk) associated with significantly lower risk of Ne (0.61 [0.41–0.91], p < 0.01; 0.49 [0.34–0.71], p < 0.001).
Blackstock (1972) [44]Cross-Sectional StudyUnited KingdomChronic Alcoholism: 30; Hospital Personnel: 14Chronic Alcoholism: 7:23; Hospital Personnel: NRChronic Alcoholism: 44.8 (21–65); Hospital Personnel: 36.6 ± 6.9Chronic alcoholism ± PoN vs. hospital personnelChronic alcohol consumption/dependencyGreater electrophysiological perturbation in those with AUD vs. hospital personnel (p < 0.001).
Callaghan (2020) [45]Cross-Sectional StudyUSBMI < 35 kg—Ne: 45; BMI > 35 kg—Ne: 110; BMI > 35 kg + Ne: 28BMI < 35 kg—Ne: 37:8; BMI > 35 kg—Ne: 87:23; BMI > 35 kg + Ne: 18:10BMI < 35 kg—Ne: 43.8 ± 12.1; BMI > 35 kg—Ne: 43.5 ± 11.2; BMI > 35 kg + Ne: 51.4 ± 9.6Ca: BMI > 35 kg ± Ne; Co: BMI < 25 kg
BMI < 35 kg—Ne; BMI > 35 kg—Ne; BMI > 35 kg + Ne		Alcohol: drinks/wk (past yr)Alcohol consumption not significantly different between Ne groups (p > 0.05).
Chang (2025) [46]Cross-Sectional StudyChinaDPN+: 163; DPN−: 107DPN+: 69:94; DPN-: 49:58DPN+: 67 (63–70); DPN−: 65 (62–69)Elderly T2DM ± DPNHistory of alcohol consumption (yes, no)Alcohol consumption not significantly correlated with DPN (p = 0.310).
Chaware (2022) [47]Cross-Sectional StudyIndia1000:10039.91Chronic alcoholism ± PNChronic alcoholism (>60 g eth/d or >15 drinks/wk): <5 yrs, 5–15 yrs, >15 yrsGreater severity of DPN significantly associated with longer consumption (<5 yrs: 21.8 ± 3.4; 5–15 yrs: 28.1 ± 3.7; >15 yrs: 33.7 ± 3.9; p = 0.001).
Ching (2024) [48]Cross-Sectional StudyMalaysiaOverall: 1283; PN−: 943; PN+: 340Overall: 635:648; PN−: 495:448; PN+: 140:20040.6 ± 12.9 (18–80)Any etiology ± PNAlcohol consumption (yes, no)Alcohol consumption not significantly different between PN groups (18.53% vs. 19.72%, p > 0.05).
Chukwubuzo (2022) [49]Cross-Sectional StudyNigeria422289:13357.6 ± 10.1T1DM or T2DM ± PNAlcohol Consumption: Yes, NoAlcohol consumption not significantly associated with painful DPN (1.48 [0.74–2.98], p < 0.05).
Claus (1985) [50]Cross-Sectional StudyGermanyChronic Alcoholism: 30; Healthy Volunteers: 30Chronic Alcoholism: 0:30; Healthy Volunteers: 2:28Chronic Alcoholism: 38.2 ± 6.4 (26–48); Healthy Volunteers: 34.9 ± 6Chronic alcohol use ± PoNHistory of alcohol consumption (up to >400 mL/d for 5–12 yrs)Alcohol consumption (>12 yrs) significantly correlated with higher PoN frequency (p = 0.007). Electrophysiology significantly impaired vs. control (p < 0.01 for all).
Correa (2023) [51]Cross-Sectional StudyBrazilOverall: 444; LLBP: 313; PNBP: 33; WP: 98Overall: 289:155; LLBP: 188:125; PNBP: 26:7; WP: 75:23Overall: 39.72 ± 14.68; LLBP: 37.02 ± 13.39; PNBP: 8.45 ± 14.30; WP: 48.78 ± 15.59Chronic BP due to any etiologyAlcohol Abuse: Yes, NoReported alcohol consumption: LLBP: 12.1%, PNBP: 9.1%, WP: 12.2% (statistics NR).
D’Amour (1991) [52]Cross-Sectional StudyCanadaChronic Alcoholism: 20; Hospital Personnel: 20NRChronic Alcoholism: 46 (31–67); Hospital Personnel: 38 (21–50)Chronic alcoholism ± PN vs. hospital personnelHistory of alcohol consumption (>10 yrs or >100 g/d)PN in 75% of AUD. Electrophysiology significantly reduced in patients with alcoholism vs. healthy hospital personnel (p < 0.05).
Estruch (1993) [53]Cross-Sectional StudySpainChronic Alcoholism: 250; Healthy Volunteers: 100Chronic Alcoholism: 0:250; Healthy Volunteers: 0:100Chronic Alcoholism: 41 ± 11 (20–65); Healthy Volunteers: 40 ± 10 (20–65)Chronic alcoholism ± PN vs. healthy volunteersDaily ethanol consumption (>100 g) over last 2 yrsPN present in 16% (41) of AUD. AUD + PN had higher ethanol consumption vs. those without PN (34.7 vs. 22.4, p < 0.001); TLDE was an independent risk factor for PN in multivariate analysis (p < 0.001).
Fernandez-Sola (1995) [54]Cross-Sectional StudySpain1000:10041 ± 9 (25–60)Chronic alcoholism ± PNDaily eth intake (g/d); duration of eth consumption; TLDEPN (39% vs. 15%, p = 0.014) and TLDE (31.7 ± 17 vs. 23.3 ± 14, p = 0.01) significantly higher in those with chronic alcoholism + type II fiber atrophy vs. without.
Gierthmühlen (2024) [55]Cross-Sectional StudyDenmark, France, Germany, Israel, Spain, UKOverall: 1181; Ne + Pain: 843; Ne − Pain: 338Overall: 405:776; Ne + Pain: 285:558; Ne − Pain: 120:218Overall: 65.8 ± 12 (19–92); Ne + Pain: 64.9 ± 12.4 (19–92); Ne − Pain: 68.1 ± 10.6 (19–87)Any etiology Ne ± painCurrent or previous alcohol misuse (yes, no)Prevalence of current or previous alcohol misuse significantly lower among those with pain vs. without (6.6% vs. 11.5%, p = 0.0022).
Gylfadottir (2020) [56]Cross-Sectional StudyDenmark55142355:315964.1 ± 10.9T2DM ± DPoNAlcohol: >7 (F)/14 (M) unitsAlcohol consumption above recommended limit not significantly associated with DPoN (0.94 [0.74–1.18], p > 0.05), or painful DPoN (1.09 [0.81–1.46], p > 0.05), in multivariable logistic regression.
Hicks (2022) [57]Cross-Sectional StudyUSOverall: 6902; With PN: 1181; Without PN: 5721Overall: 3589:3313; With PN: 443:738; Without PN: 3101:2620% (!) 40–49: 36 (0.9); 50–59: 27.8 (0.8); 60–69: 18.2 (0.6); 70–79: 12.8 (0.4); ≥80: 5.2 (0.3)DM ± PNAlcohol: Never, Former, CurrentAlcohol consumption reported between PN groups: Never: 16.4%, Former: 27.2%, Current: 56.5% vs. 11.8%, 20.9%, 67.3% (statistics NR).
Ireri (2024) [58]Cross-Sectional StudyKenya314182:13258.49 ± 17.43DM ± NeHistory of alcohol consumptionAlcohol consumption not significantly associated with Ne (p = 0.481).
Jeyam (2020) [59]Cross-Sectional StudyScotlandOverall: 5558; With DPN 715; Without DPN 4842Overall: 2449:3109; With DPN: 320:395; Without DPN 2129:2713^ Overall: 44.7 (33, 55.2); With DPN: 50.6 (41, 59.3); Without DPN: 43.7 (32, 54.4)T1DM ± DPNAlcohol (u/wk): 2–6, 6–14, 14–21, 21–32, >32Alcohol consumption below 32 u/wk associated with lower odds of DPN (0.47 [0.29–0.75], p < 0.05), while above 32 u/wk was not (0.88 [0.56–1.38], p > 0.05). Authors suggest reverse causation–protopathic bias.
Li (2023) [60]Cross-Sectional StudyChinaOverall: 25,710; With PDPN: 14,699; Without PDPN: 11,011Overall: 10,785:14,925; With PDPN: 6240:8459; Without PDPN: 4545:6466^ Overall: 63 (55, 71); With PDPN: 65 (56, 73); Without PDPN: 61 (53, 69)T2DM ± PDPNAlcohol Abuse: Yes, NoPDPN significantly lower with alcohol abuse vs. without (54.1% vs. 57.1%, p = 0.002). Authors suggest reverse causation–protopathic bias.
Mawdsley & Mayer (1965) [61]Cross-Sectional StudyUSChronic Alcoholism: 76; Healthy Personnel: 105Chronic Alcoholism: 12:64; Healthy Personnel: NRChronic Alcoholism: 25–69; Healthy Personnel: 20–70Chronic alcohol use ± PNHistory of alcohol consumption (1 pint whisky to 1 gallon wine/d)Electrophysiology significantly diminished vs. control (p < 0.001 for all).
McCulloch (1980) [62]Cross-SectionalScotland5410:54144 ± 11.6 (20–59)DM ± PNAlcohol Intake: Moderate (6 drinks/yr to 10 drinks/wk) vs. Excessive (3–4 drinks/d to diagnosed alcoholism)PN significantly higher in DM men with excessive alcohol consumption vs. those with moderate (36% vs. 14%, p < 0.001) and most evident with shorter durations of DM (<5 yrs: 32% vs. 8%, p < 0.001).
Melgaard (1986) [63]Cross-Sectional StudyDenmark4680:46845“Normal” population ± PoNAlcohol questionnaire including duration and frequency of useDependence-related behaviors were significantly correlated with disturbed electrophysiology (p < 0.05).
Mellion (2014) [64] Cross-Sectional StudyUSOverall: 18; Heavy Drinkers: 9; Healthy Co: 99:9Heavy Drinkers: 35.4; Healthy Co: 43.3Heavy alcohol drinking (>5 drinks/d (M), >4 drinks/d (F)) + PN vs. healthy coEth consumed daily (g); Average duration heavy drinkingIndividuals with a history of heavy alcohol consumption exhibited diminished electrophysiology, compared to those without (p < 0.05).
Mick (2020) [65]Cross-Sectional StudyFrance, Italy, Spain, UK1030651:37960.2 ± 15.32; ^ 61 (49–72)Localized NP due to any etiologyAlcohol Abuse/Dependence: Current, Past, NeverCurrent or past alcohol dependence/abuse was reported in 6.36% of patients with NP (further statistics NR).
Mills (1986) [66]Cross-Sectional StudyUK194:15(30–71)Chronic alcoholism ± PNHistory of alcoholism (120 g eth/d for 4+ yrs)Chronic alcohol consumption (>100 g/d) significantly associated with electrophysiological PN in 12/19 (statistics NR).
Monforte (1995) [67]Cross-Sectional StudySpainAlcohol-Dependent: 107; Healthy Reference: 61Alcohol-Dependent: 18:89; Healthy Reference: 10:51Alcohol-Dependent: 43 ± 11; Healthy Reference: 41 ± 14Chronic alcohol use ± PNHistory of alcohol consumption (>100 g/d (M) or >80 g/d (F) for >2 yrs)Electrophysiological PN identified in 36.8% of alcohol-dependent individuals vs. 1 control (1.64%), p < 0.001). Diminished electrophysiology correlated with greater TLDE (r = −0.43, p < 0.001).
Nagakura (2023) [68]Ecological Cross-Sectional StudyJapanPregabalin Reimbursement Claims per 1000 population; up to 126 millionNR(40–74)NP due to any etiology treated with pregabalinAlcohol: Daily, Sometimes, Rarely/NeverExcessive alcohol consumption significantly associated with prevalent NP (β = 0.2683, p < 0.01); low-to-moderate intake reduced prevalence (r = −0.4713, p < 0.01); daily intake increased prevalence (r = 0.6253, p < 0.01).
Nicolosi (2005) [69]Cross-Sectional StudyItaly404:3649.2 ± 10.3 (33–76)Chronic alcohol use ± SoNHistory of alcohol consumption (100–400 g/d for 5–25 yrs)SoN in 62.5% (25). Electromyography scores were statistically significantly positively correlated with TLDE (r = 0.35, p < 0.03).
Nielsen (2022) [70]Cross-Sectional StudyDenmark2839High CIPN Score: 274:146; Low CIPN Score: 1193:870^^ High CIPN Score: 69; Low CIPN Score: 67; (18–99)Cancer diagnosis at any stage of treatment ± CIPNAlcohol: yes/no + u/wkAlcohol consumption significantly different between CIPN groups (60.2% vs. 73.5%, p < 0.001); high consumption (>14 u/wk) significantly associated with high CIPN20 scores in males (22% vs. 11%, p = 0.002).
Papantoniou (2024) [71]Cross-Sectional StudyGreece9034:5651.98 ± 8.86 (27–74)AUD ± PNDuration of Abuse; Total Alcohol Units (kg alcohol/lifetime)Alcohol abuse significantly longer in those with Ne vs. without (8.08 ± 7.25 vs. 6.92 ± 4.38, p = 0.024), and in those with impaired electrophysiology (p = 0.02).
Revesz (2022) [72]Cross-Sectional StudyThe NetherlandsOverall: 1516; With PN: 980; Without PN: 536Overall: 634:882; With PN: 445:535; Without PN: 189:347Overall: 69.1 ± 9.4; With PN: 70.1 ± 9.4; Without PN: 67.2 ± 9.2Colorectal cancer survivors ± PNAlcohol Consumption: Drinks/wkAlcohol intake significantly lower in individuals with PN vs. without (median 4 vs. 5 drinks/wk, range 0–100 vs. 0–50, p = 0.006) in univariate analysis only.
Sahito (2022) [73]Cross-Sectional StudyPakistanOverall: 1057; With PN: 607; Without PN: 450Overall: 414:643; With PN: 230:377; Without PN: 184:26630–40: 119; 41–50: 316; 51–60: 324; 61–70: 165; >70 yrs: 133T2DM ± PNHistory of alcohol intake: Yes, NoAlcohol intake reported between PN groups: 4.7% vs. 1.4% (statistics NR).
Shetty (2025) [74]Cross-Sectional StudyIndia1109:10141.5 ± 11.9 (22–84)Chronic liver disease ± PNHistory of alcohol consumption (≥5 yrs)Duration (13.9 ± 6.1 yrs vs. 9.6 ± 4.6 yrs, p < 0.05), and quantity of alcohol consumption significantly higher in those with PN vs. without.
Srivastava (2022) [75]Cross-Sectional StudyIndia9879:1951.63 ± 10.68Cancer survivors ± CIPNHistory of alcohol consumption: Yes (current, former), NoHistory of alcohol consumption not significantly associated with CIPN sensory/motor severity (18.37% vs. 81.63%, p > 0.05).
Trendowski (2021) [76]Cross-Sectional StudyUSWith CIPN: 550; Without CIPN: 495With CIPN: 440:110; Without CIPN: 355:140^^ With CIPN: 56 (23–79); Without CIPN: 58 (21–79)African American cancer survivors ± CIPNAlcohol: yes (previous 4 wks)/no; Alcohol Consumed (drinks/wk): 0–4, ≥5Alcohol consumption, drinks/d, not significantly associated with CIPN (aPR: 0.88 [0.68–1.14], p = 0.32; aPR: 0.99 [0.91–1.07], p = 0.73).
Van der Velde (2020) [77]Cross-Sectional StudyThe NetherlandsOverall: 2401; High Sural SNAPA: 793; Med Sural SNAPA: 796; Low Sural SNAPA: 812Overall: 1174:1227; High Sural SNAPA: 464:329; Med Sural SNAPA: 377:419; Low Sural SNAPA: 334:478Overall: 59.3 ± 8.2; High Sural SNAPA: 56.4 ± 8.2; Med Sural SNAPA: 59.4 ± 7.9; Low Sural SNAPA: 62 ± 7.5T2DM ± PNAlcohol: >7 (F)/14 (M) unitsAlcohol consumption reported between PN groups: High: 26.7%, Medium: 25.8%, Low: 27.6% (statistics NR).
Villalta (1989) [78]Cross-Sectional StudySpainChronic Alcoholism: 70; Hospital Personnel: 70Chronic Alcoholism: 0:70; Hospital Personnel: NRChronic Alcoholism: 39.7 ± 9.6 (20–60); Hospital Personnel: 39.2 ± 11 (20–59)Chronic alcoholism + PN vs. hospital personnelHistory of alcohol consumption (>100 g/d for >2 yrs)Prevalence of PN in 37% (21/56). Motor CV significantly negatively correlated with TLDE (r = −0.28, p < 0.05).
Vittadini (2001) [79]Cross-Sectional StudyItaly29687:20945.2 ± 11.2 (20–77)Chronic alcohol use ± PoNHistory of alcohol consumption (>100 g/d)Prevalence of electrophysiological PoN in 48.6% (144/296). PoN severity increased as duration of alcohol misuse lengthened (19.8% at 5 yrs to 40.4% at 10 yrs, p < 0.05).
Wang (2023) [80]Cross-Sectional StudyChinaOverall: 14,908; With DPN: 10,084; Without DPN: 4824Overall: 6322:8586; With DPN: 4365:5719; Without DPN: 1957:2867Overall: 61.3 ± 13, ^ 62 (53, 70); With DPN: 62.6 ± 12.5, ^ 63 (55, 71); Without DPN: 58.5 ± 13.5, ^ 59 (50, 67)T2DM ± DPNAlcohol Abuse (Pure Consumption in g/d): >40 (F)/60 (M); Never, Former, CurrentAlcohol abuse significantly lower among those with DPN vs. without (8.2% vs. 11%, p < 0.001).
Wetterling (1999) [81]Cross-Sectional StudyGermany24164:177F: 43.8 ± 8.8; M: 41 ± 9.9Chronic alcohol use ± PoNHistory of alcohol consumption: episodic (<1 d/wk), frequent (>3 d/wk), continuous (daily)Prevalence of PoN increased with increasing alcohol consumption (11.3%, 29.6%, 29.9%, p = 0.025), and TLDE (p = 0.0104).
Wilson & Thompson (2021) [82]Cross-Sectional StudyUKDetoxification+: 17; Detoxification−: 13Detoxification+: 6:11; Detoxification−: 6:7Detoxification+: 46.8 ± 9 (37–64); Detoxification−: 54.5 ± 10.5 (30–70)High-risk alcohol use ± history of detoxification ± NPHigh-risk alcohol use via FAST score ≥ 3Prevalence of NP (IDPQ ≥ 3) significantly greater in those with history of detoxification (8/9) vs. those without (1/12), p = 0.04.
Wu (2025) [83]Cross-Sectional StudyUSOverall: 1068; MNSI+: 666; MNSI−: 402641:42784.1 (78–100)Very old adults ± PNAlcohol: Never, Former, CurrentCurrent, former alcohol use not associated with MNSI-defined neuropathy (0.90 [0.59–1.37], 1.02 [0.67–1.54], respectively). Former use not associated with monofilament insensitivity (0.78 [0.52–1.16]), whereas current use was (0.65 [0.43–0.98]).
Yokoyama (2020) [84]Cross-Sectional StudyJapanOverall: 9914; Without DPoN: 6180; With DPoN: 2745 (with DPoNS: 1689; with UDoPN: 989)Overall: 3715:6139; Without DPoN: 2273:3904; With DPoN: 1041:1705 (with DPoNS: 664:1025, with UDPoN: 397:530)^^ Overall: 66 (69–73); Without DPoN: 65 (57–71); With DPoN: 70 (63–77) (with DPoNS: 69 (63–76), with UDPoN: 67 (59–75))T2DM ± DPoNAlcohol: Current, Former, NeverFormer alcohol consumption associated with higher odds of DPN (2.02 [1.25–3.27], p = 0.004), while current was not. Authors suggest reverse causation–protopathic bias.
Zahr (2019) [85]Cross-Sectional StudyUSCa: 154; Co: 99Ca: 43:111; Co: 41:58Ca: 49.8 ± 10.5 (21–77); Co: 50.9 ± 13.3 (21–74)Ca: AUD ± PN; Co: healthy ± PNHistory of AUDPrevalence of PN (Ca: 20 vs. 134; Co: 3 vs. 96; p = 0.007), vibration perception impairment (Ca: 41 vs. 113; Co: 15 vs. 84; p = 0.03), greater with history of AUD.
Zambelis (2005) [86]Cross-Sectional StudyGreece9822:1745.2 ± 9.9 (27–70)Chronic alcohol dependence ± PoNDaily alcohol consumption (g); duration of alcohol abuseDuration of alcohol consumption significantly higher in those with PoN vs. without (19.19 vs. 14.14, p = 0.03).
Zambelis (2016) [87]Cross-Sectional StudyGreece9923:7647 ± 19.6Alcohol dependence ± Ulnar NeDuration of alcohol dependenceUNE significantly associated with duration of alcohol dependence (1.09 [1.04–1.15], p < 0.001).
APA: action potential amplitude; aPR: adjusted prevalence ratio; aRR: adjusted risk ratio; AUD: alcohol use disorder; BMI: body mass index; BP: back pain; Ca: cases; CAN: cardiovascular autonomic neuropathy; CIDP: chronic inflammatory demyelinating polyradiculoneuropathy; CIPN: chemotherapy-induced peripheral neuropathy; CIPN20: European Organization for Research and Treatment of Cancer CIPN 20-item scale; Co: controls; CP: chronic pain; CRPS: complex regional pain syndrome; CV: conduction velocity; d: day; DL: distal latency; DM: diabetes mellitus; DPN: diabetic peripheral neuropathy; DPoN: diabetic polyneuropathy; DPoNS: diabetic polyneuropathy-related sensory symptoms/signs; DSN: distal symmetric neuropathy; DSPoN: distal sensory polyneuropathy; eth: ethanol; F: female; FAST: Fast Alcohol Screening Tests; g: grams; IDDM: insulin-dependent diabetes mellitus; IDPQ: Identification of Pain Questionnaire; IENFD: intraepidermal nerve fiber density; kg: kilogram; LLBP: localized lower back pain; M: males; mL: milliliter; MNSI: Michigan Neuropathy Screening Instrument; mo: month; m/s: meters per second; MSK: musculoskeletal pain; Ne: neuropathy; ND: neurophysiologically deteriorated; NIDDM: non-insulin-dependent diabetes mellitus; NP: neuropathic pain; NR: not reported; PDPN: painful diabetic peripheral neuropathy; PN: peripheral neuropathy; PNBP: peripheral neuropathic back pain; PoN: polyneuropathy; PSN: peripheral sensory neuropathy; PSUD: polysubstance use disorder group (tobacco, alcohol, +1 other); r: Pearson’s correlation; SE: standard error; SEP: sensory evoked potential; SFN: small fiber neuropathy; SNAPA: sensory nerve action potential amplitude; SoN: somatic neuropathy; T1DM: type 1 diabetes mellitus; T2DM: type 2 diabetes mellitus; TAUD: tobacco and alcohol use disorder group; TLDA/E: total lifetime dose of alcohol/ethanol (always reported as kg alcohol/ethanol/kg body weight unless otherwise specified); TUD: tobacco use disorder group; u: units; UDPoN: unknown status diabetic polyneuropathy; UN: ulnar neuropathy; UNE: ulnar neuropathy at the elbow; VPT: vibration perception threshold; wk: week; WP: widespread pain; x2: Chi-Square statistic; yr(s): year(s); β: beta coefficient; μV: microvolts; ^: median (interquartile range); ^^: median (range); !: standard error; all data reported as mean ± SD, mean (range), or mean [95% CI]; outcome data reported as cases vs. controls, or as “with Ne” vs. “without Ne”, with OR [95% CI], p-value (adj p-value when available) unless otherwise specified. Disease duration always reported in years, unless otherwise specified.
Table 2. Summary of findings.
Table 2. Summary of findings.
Incidence of Neuropathy with/without Alcohol Consumption
Population(s): Type 1 diabetes mellitus ± diabetic peripheral neuropathy; type 1 diabetes mellitus ± neuropathy; complex regional pain syndrome and/or musculoskeletal pain via trauma; cancer survivors ± chemotherapy-induced peripheral neuropathy; type 2 diabetes mellitus + hypertension ± neuropathy; diabetes mellitus ± incident neuropathy; type 2 diabetes mellitus ± diabetic polyneuropathy ± pain; diabetes mellitus ± neurophysiologically deteriorated
Intervention: Alcohol
Comparison: No alcohol
Outcome: Neuropathy incidence
Setting: Denmark, Finland, Germany, US
Study Design: Cohort Studies
StratificationNo. of studiesNeuropathy Positive (%)Neuropathy Negative (%)Odds ratio
(95% CI)		Relative risk
(95% CI)		Risk of biasIncIndImpCertainty of evidence (GRADE)References
Consumed Alcohol3483/1369
(35.28%)		451/1515
(29.77%)		1.29
(1.10–1.50)		1.14
(1.05–1.23)		SeriousHigh riskLow riskLow riskVery Low
⨁◯◯◯		Braffett (2020) [13], Kindl (2021) [22], Sreeram (2023) [25]
Alcohol Dependency31054/49,327
(2.14%)		3306/191,627
(1.73%)		1.24
(1.16–1.33)		1.19
(1.12–1.25)		SeriousMod
risk		Low riskLow riskVery Low
⨁◯◯◯		Adler (1997) [12], Iturralde (2024) [19], Khan (2023) [21]
Overconsumption by Guidelines2354/398
(88.94%)		550/653
(84.23%)		1.51
(1.04–2.2)		1.31
(1.02–1.71)		SeriousLow riskMod riskMod
risk		Very Low
⨁◯◯◯		Christensen (2020) [14], Lehtinen (1993) [24]
Association between Neuropathy and Alcohol Consumption
Population(s): Diabetes mellitus ± peripheral neuropathy; chronic inflammatory demyelinating polyradiculoneuropathy; ulnar neuropathy at the elbow; non-insulin-dependent diabetes mellitus ± distal symmetric neuropathy; paresthesia ± small fiber neuropathy; alcoholism ± peripheral neuropathy; healthy controls
Intervention: Alcohol
Comparison: No alcohol
Outcome: Neuropathy association
Setting: Ethiopia, France, Italy, US
Study Design: Case–Control Studies
StratificationNo. of studiesNeuropathy Positive (%)Neuropathy Negative (%)Odds ratio
(95% CI)		Relative risk
(95% CI)		Risk of biasIncIndImpCertainty of evidence (GRADE)References
Consumed Alcohol4271/756 (35.85%)487/1117 (43.60%)0.82
(0.73–0.92)		---SeriousMod riskHigh riskMod riskVery Low
⨁◯◯◯		Gebabo (2021) [32], Doneddu (2020) [28], Franklin (1994) [30], Mondelli (2020) [35]
Alcohol Dependency232/194
(16.49%)		30/219
(13.70%)		1.24
(0.73–2.15)		---Not SeriousLow riskMod riskHigh riskVery Low
⨁◯◯◯		Fouchard (2023) [29], Pessione (1995) [36]
Prevalence of Neuropathy with/without Alcohol Consumption
Population(s): Alcohol use disorder ± peripheral neuropathy; diabetes mellitus ± neuropathy and/or peripheral neuropathy; chronic back pain; type 1 diabetes mellitus ± neuropathy; type 2 diabetes mellitus ± diabetic peripheral neuropathy; diabetes mellitus ± diabetic polyneuropathy; chemotherapy-induced peripheral neuropathy; chronic neck/shoulder/upper limb pain
Intervention: Alcohol
Comparison: No alcohol
Outcome: Neuropathy prevalence
Setting: Brazil, China, Denmark, Europe, Japan, Kenya, Malaysia, Netherlands, Pakistan, Scotland, US
Study Design: Cross-Sectional Studies
StratificationNo. of studiesNeuropathy Positive (%)Neuropathy Negative (%)Odds ratio
(95% CI)		Relative risk
(95% CI)		Risk of biasIncIndImpCertainty of evidence (GRADE)References
Consumed Alcohol123548/6789
(52.26%)		15,261/22,298
(68.44%)		0.50
(0.48–0.53)		---SeriousMod riskMod riskLow riskVery Low
⨁◯◯◯		Alessi (2020) [39], Asai (2022) [42], Beulens (2008) [43], Chang (2025) [46], Ching (2024) [48], Correa (2023) [51], Hicks (2022) [57], Ireri (2024) [58], Jeyam (2020) [59], Nielsen (2022) [70], Sahito (2022) [73], Yokoyama (2020) [84]
Alcohol Dependency3899/10,175
(8.84%)		716/5154
(13.89%)		0.60
(0.54–0.67)		---SeriousHigh riskLow riskLow riskVery Low
⨁◯◯◯		Monforte (1995) [67], Wang (2023) [80], Zahr (2019) [85]
Overconsumption by Guidelines2358/1728
(20.72%)		896/5052
(17.74%)		1.21
(1.06–1.39)		---SeriousLow riskMod riskLow riskVery Low
⨁◯◯◯		Gylfadottir (2020) [56], Velde (2020) [77]
CI: confidence interval; Imp: imprecision; Inc: inconsistency; Ind: indirectness; No.: number; GRADE Working Group grades of evidence: High certainty (we are very confident that the true effect lies close to that of the estimate of the effect); moderate certainty (we are moderately confident in the effect estimate—the true effect is likely to be close to the estimate of the effect, but there is a possibility that it is substantially different); low certainty (our confidence in the effect estimate is limited—the true effect may be substantially different from the estimate of the effect); very low certainty (we have very little confidence in the effect estimate—the true effect is likely to be substantially different from the estimate of effect).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Klowak, M.; Bado, E.J.; Reid-John, A.; Dawood, R.; Madakadze, C.; Boggild, A.K. A Systematic Review of Lifestyle Interventions for Neuropathy and Neuropathic Pain: Alcohol Consumption and Avoidance. Brain Sci. 2026, 16, 551. https://doi.org/10.3390/brainsci16060551

AMA Style

Klowak M, Bado EJ, Reid-John A, Dawood R, Madakadze C, Boggild AK. A Systematic Review of Lifestyle Interventions for Neuropathy and Neuropathic Pain: Alcohol Consumption and Avoidance. Brain Sciences. 2026; 16(6):551. https://doi.org/10.3390/brainsci16060551

Chicago/Turabian Style

Klowak, Michael, Ezra J. Bado, Aquilla Reid-John, Rumaysa Dawood, Candice Madakadze, and Andrea K. Boggild. 2026. "A Systematic Review of Lifestyle Interventions for Neuropathy and Neuropathic Pain: Alcohol Consumption and Avoidance" Brain Sciences 16, no. 6: 551. https://doi.org/10.3390/brainsci16060551

APA Style

Klowak, M., Bado, E. J., Reid-John, A., Dawood, R., Madakadze, C., & Boggild, A. K. (2026). A Systematic Review of Lifestyle Interventions for Neuropathy and Neuropathic Pain: Alcohol Consumption and Avoidance. Brain Sciences, 16(6), 551. https://doi.org/10.3390/brainsci16060551

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop