Association between magnesium depletion score and overactive bladder among U.S. Adults using data from NHANES 2005–2018

Abstract

Overactive bladder (OAB) is a common condition that significantly affects quality of life. Magnesium deficiency may influence muscle and nerve functions, potentially contributing to bladder dysfunction. This study aimed to examine whether magnesium depletion is associated with OAB symptoms among U.S. adults. We analyzed data from 28,621 participants aged 20–80 years in the National Health and Nutrition Examination Survey (NHANES) 2005–2018. OAB symptoms were assessed using a standardized questionnaire, and magnesium depletion was evaluated using a magnesium depletion score (MgDS). Logistic regression models adjusted for demographic, lifestyle, and clinical factors were employed to explore the association. Higher MgDS was significantly associated with an increased risk of OAB. In the fully adjusted model, each one-point increase in MgDS was linked to 9% higher odds of OAB (OR = 1.09, 95% CI 1.03–1.15, p = 0.002). Compared to the low MgDS group, individuals in the middle MgDS group had 17% higher odds of OAB (OR = 1.17, 95% CI 1.03–1.33, p = 0.02), while those in the high MgDS group had 20% higher odds (OR = 1.20, 95% CI 1.05–1.38, p = 0.01). Subgroup analyses indicated that this association was particularly pronounced in females, non-smokers, middle-aged adults (40–60 years), and individuals with obesity (BMI ≥ 30 kg/m²). Our findings suggest that magnesium depletion is associated with increased OAB risk in U.S. adults; however, due to the cross-sectional nature of this study, causality cannot be inferred and further prospective studies are needed.

Supplementary Information

The online version contains supplementary material available at 10.1038/s41598-025-17962-7.

Introduction

Overactive bladder (OAB) is a prevalent lower urinary tract storage disorder characterized by urgency, defined as a sudden, uncontrollable urge to urinate, often accompanied by increased urinary frequency and nocturia. In some cases, urgency urinary incontinence may also occur, without the presence of urinary tract infections or other identifiable urological conditions^1,2. In the United States, OAB affects approximately 16.0% of men and 16.9% of women³. Its prevalence increases with age and significantly impacts patients’ quality of life, sleep patterns, and mental health^3–5. Despite available treatment options, current therapies often fail to provide sufficient relief and are associated with adverse effects. Additionally, the growing aging population has led to a rising OAB burden, posing a significant healthcare challenge. Studies indicate that OAB-related healthcare costs in the U.S. are more than 2.5 times higher than those for individuals without OAB, and this disparity is even greater among those with chronic age-related comorbidities⁶.

Several lifestyle and dietary factors have been implicated in the development of OAB, including obesity, smoking, fluid intake, carbonated beverage consumption, and dietary patterns⁷. In addition to these traditional risk factors, emerging evidence suggests that immune-inflammatory responses may contribute to OAB pathogenesis^8,9. Inflammation can lead to heightened peripheral afferent nerve excitability, which in turn triggers key OAB symptoms such as urinary urgency and frequency¹⁰. This highlights inflammation as a potential underlying mechanism in OAB development. Magnesium is an essential element that plays a critical role in maintaining overall health and homeostasis¹¹. Since the human body cannot produce magnesium, it must be continuously replenished through dietary intake and drinking water. Magnesium deficiency has been implicated as a potential contributor to bladder dysfunction, as it is crucial for neuromuscular regulation, inflammation modulation, and smooth muscle relaxation¹². A deficiency in magnesium may lead to increased detrusor muscle excitability, predisposing individuals to bladder hyperactivity¹³. Additionally, magnesium possesses unique antioxidant and anti-inflammatory properties, which may help mitigate bladder dysfunction¹⁴. Studies have suggested that magnesium depletion can induce neuroinflammation and bladder-related pain, indicating a potential link between low magnesium levels and OAB symptoms¹⁵.

Although magnesium deficiency has been linked with various health conditions, existing methods for assessing magnesium status—such as serum magnesium concentration or single dietary assessments—have critical limitations. Serum magnesium measurements often fail to detect mild to moderate chronic depletion because serum levels can remain normal despite substantial intracellular deficits. Similarly, single dietary recall methods cannot accurately reflect long-term dietary habits or chronic magnesium deficiency. To address these gaps, the magnesium depletion score (MgDS) was developed as a comprehensive clinical tool integrating multiple factors influencing magnesium metabolism, including proton pump inhibitor (PPI) use, diuretic use, alcohol consumption, and kidney disease¹⁶. Compared to conventional approaches, MgDS may better reflect chronic magnesium depletion and its clinical implications¹⁶. Current research has demonstrated significant associations between MgDS and multiple health conditions, including systemic inflammation, cardiovascular disease (CVD), chronic kidney disease, metabolic syndrome, hypertension, and diabetes^16–21. However, the association between MgDS and OAB remains unexplored, highlighting a clear research gap that the current study aims to fill.

Given its physiological significance, MgDS has been proposed as a comprehensive indicator of magnesium status and its potential impact on health outcomes. However, its relationship with OAB remains unexplored. This study aims to investigate the association between MgDS and OAB using nationally representative data from the National Health and Nutrition Examination Survey (NHANES) 2005–2018.

Methods

Study design and population

This study utilized data from the National Health and Nutrition Examination Survey (NHANES), a nationally representative program conducted by the National Center for Health Statistics (NCHS) to assess the health and nutritional status of the U.S. population. The NHANES dataset is publicly available through the Centers for Disease Control and Prevention (CDC) website (https://www.cdc.gov/nchs/nhanes/). The survey employs a complex, stratified, multistage probability sampling design, ensuring that the selected participants represent the non-institutionalized U.S. population. NHANES data are collected and released in biennial cycles, with each cycle containing a combination of interview-based questionnaires, physical examinations, and laboratory tests. The study was conducted in accordance with the Declaration of Helsinki and approved by the National Center for Health Statistics Ethics Review Board (Protocol #2011-07 and Continuation of Protocol #2011-07). Informed consent was obtained from all participants involved in the study.

For this analysis, we pooled data from seven NHANES cycles (2005–2006, 2007–2008, 2009–2010, 2011–2012, 2013–2014, 2015–2016, and 2017–2018), comprising a total of 70,190 participants. Participants were excluded if they were younger than 20 years old (n = 30,441), pregnant women (n = 566), lacked complete OAB assessment data (n = 5,397), had missing MgDS data (n = 1,230), or had incomplete covariate data (n = 3,935). After applying these exclusion criteria, a total of 28,621 participants were included in the final analysis, of whom 5,674 exhibited OAB symptoms (Fig. 1).

Fig. 1.

Flowchart of the sample selection process. NHANES, National Health and Nutrition Examination Survey.

Assessment of magnesium depletion score

The MgDS is a clinical composite index designed to assess magnesium deficiency based on four established risk factors¹⁶. These factors include diuretic use, proton pump inhibitor (PPI) use, renal function, and heavy alcohol consumption.

The MgDS is a validated clinical index designed to reflect chronic magnesium depletion risk by combining multiple clinical factors known to influence magnesium homeostasis. MgDS calculation includes the following step-by-step criteria (Figure S1): (1) Diuretic use: Participants using diuretics scored 1 point; no diuretic use scored 0 points. (2) PPI use: Participants using PPIs scored 1 point; non-users scored 0 points. (3) Renal function assessment: Estimated glomerular filtration rate (eGFR) categories scored as follows: eGFR ≥ 90 mL/min/1.73 m² scored 0 points; eGFR ≥ 60 and < 90 mL/min/1.73 m² scored 1 point; eGFR < 60 mL/min/1.73 m² scored 2 points. (4) Alcohol consumption: Heavy alcohol use (defined as > 2 drinks/day for men and > 1 drink/day for women) scored 1 point; other consumption levels (never, former, mild, moderate) scored 0 points²².

The total MgDS was calculated as the sum of these scores, providing an estimate of the severity of magnesium depletion. Based on MgDS values, participants were categorized into three groups: low MgDS (0–1 points), middle MgDS (2 points), and high MgDS (≥ 3 points). This classification allows for a more refined evaluation of magnesium status and its potential association with health outcomes, including OAB.

Assessment of overactive bladder

OAB is defined as an overactive voiding reflex characterized by urgency urinary incontinence (UUI) and nocturia. Trained interviewers conducted face-to-face interviews using a standardized questionnaire to assess OAB symptoms. The presence and severity of UUI were determined based on two key questions: “In the past 12 months, have you leaked or lost control of your urine, even a small amount, because you could not reach the toilet quickly enough due to a sudden urge or pressure to urinate?” and “How often has this occurred?” Nocturia burden was evaluated using the question: “During the past 30 days, from the time you went to bed at night until you got up in the morning, how many times did you typically wake up to urinate?” In addition to individual symptom assessment, the Overactive Bladder Symptom Score (OABSS) was used to further classify OAB status. Participants with a total OABSS of ≥ 3 points were considered to have OAB. This validated approach aligns with previous applications of NHANES data in OAB research, ensuring consistency and reliability in symptom evaluation^23,24.

Other covariates

Both continuous and categorical variables were considered as potential covariates in this study. Continuous variables included age, body mass index (BMI), and poverty-income ratio (PIR). Categorical variables encompassed sex (female and male), race/ethnicity (Mexican American, non-Hispanic White, non-Hispanic Black, other Hispanic, and other races), marital status (solitude or cohabitation), education level (less than high school, high school graduate, and above high school), smoking status (never, former, and current), and alcohol consumption (never, former, mild, moderate, and heavy drinker). Additionally, the presence of chronic conditions was accounted for, including hypertension (yes or no), diabetes (no, borderline, or diagnosed), hyperlipidemia (yes or no), cardiovascular disease (CVD; yes or no), and stroke (yes or no). To facilitate subgroup analyses, age was categorized into < 40 years, 40–60 years, and ≥ 60 years; BMI was classified as normal (< 25 kg/m²), overweight (25–30 kg/m²), and obese (≥ 30 kg/m²); and PIR was stratified into < 1.3, 1.3–3.5, and ≥ 3.5. This comprehensive consideration of demographic, socioeconomic, lifestyle, and health-related factors ensured a robust adjustment for potential confounders in the analysis.

Statistical analysis

Baseline characteristics were presented as means ± standard error (SE) for continuous variables and proportions for categorical variables. Differences between groups were assessed using weighted Student’s t-tests for continuous variables and weighted χ2 tests for categorical variables. Survey-weighted multivariable logistic regression models were used to evaluate the potential association between MgDS and OAB, considering MgDS both as a continuous variable and as a categorical variable (low, middle, and high MgDS groups). Three models with different levels of adjustment were constructed. Model 1 was unadjusted, without any covariate adjustments. Model 2 was partially adjusted for age, sex, race, marital status, educational level, PIR, and BMI. Model 3 was fully adjusted for age, sex, race, marital status, educational level, PIR, BMI, smoking status, alcohol consumption, and history of diabetes, CVD, hypertension, hyperlipidemia, or stroke. To explore potential effect modification, stratified and interaction analyses were conducted, considering age, sex, race, marital status, educational level, PIR, BMI, smoking status, hypertension, and CVD as stratification factors. In subgroup and interaction analyses, fully adjusted logistic regression models (Model 3) were applied within each subgroup. All covariates from Model 3 were included, except the stratifying variable, which was omitted from adjustment to avoid overadjustment within the stratum. To address missing values in covariates, we performed multiple imputation using chained equations under the assumption that data were missing at random (MAR).

All statistical analyses were performed using R version 4.2.2 (http://www.R-project.org, R Foundation) and EmpowerStats (http://www.empowerstats.com, X&Y Solutions, Inc.). A P-value < 0.05 was considered statistically significant.

Results

Baseline characteristics of study participants

This study included 28,621 participants, and baseline characteristics stratified by OAB status are shown in Table 1. Compared to non-OAB participants, those with OAB were older (57.96 ± 0.35 vs. 45.26 ± 0.24 years, p < 0.0001), more likely to be female (62.03% vs. 48.59%, p < 0.0001), and had a higher magnesium depletion score (MgDS) (1.20 ± 0.02 vs. 0.76 ± 0.01, p < 0.0001). Significant differences were also observed in education level, BMI, smoking status, and alcohol consumption (all p < 0.0001).

Table 1.

Weighted characteristics of study population based on OAB diagnosis.

Characteristics	Total participants	Non-OAB	OAB	P value
	28,621	22,947	5674
Age, years	47.21 ± 0.25	45.26 ± 0.24	57.96 ± 0.35	< 0.0001
PIR	3.05 ± 0.03	3.14 ± 0.03	2.60 ± 0.05	< 0.0001
BMI, kg/m2	29.09 ± 0.08	28.69 ± 0.09	31.28 ± 0.16	< 0.0001
MgDS	0.83 ± 0.01	0.76 ± 0.01	1.20 ± 0.02	< 0.0001
Age group, %				< 0.0001
< 40y	36.35	40.27	14.74
40–60y	38.31	38.67	36.31
≥ 60y	25.34	21.06	48.95
Gender, %				< 0.0001
Female	50.66	48.59	62.03
Male	49.34	51.41	37.97
Race, %				< 0.0001
Mexican American	7.87	8.01	7.06
Non-Hispanic White	69.80	70.41	66.44
Non-Hispanic Black	10.54	9.46	16.53
Other Hispanic	5.02	4.99	5.19
Other races	6.77	7.13	4.79
Marital status, %				< 0.0001
Solitude	36.14	35.25	41.01
Cohabitation	63.86	64.75	58.99
Education, %				< 0.0001
Less than high school	14.76	13.00	24.43
High school	23.20	22.78	25.52
Above high school	62.04	64.22	50.04
PIR, %				< 0.0001
< 1.3	20.24	18.78	28.32
1.3–3.5	35.64	34.84	40.05
> = 3.5	44.12	46.38	31.63
BMI, %				< 0.0001
Normal (< 25 kg/m2)	29.66	31.35	20.32
Overweight (25–30 kg/m2)	32.70	33.18	30.04
Obese (≥ 30 kg/m2)	37.64	35.47	49.64
Smoke, %				< 0.0001
Never	54.84	56.00	48.41
Former	24.97	24.04	30.13
Current	20.19	19.96	21.46
Alcohol consumption, %				< 0.0001
Never	10.32	9.70	13.77
Former	13.29	11.82	21.39
Mild	36.97	37.33	35.00
Moderate	17.78	18.35	14.66
Heavy	21.63	22.80	15.17
Hypertension, %				< 0.0001
No	62.29	66.13	41.09
Yes	37.71	33.87	58.91
Diabetes, %				< 0.0001
No	77.99	80.81	62.42
Borderline	8.19	7.87	10.00
Yes	13.82	11.32	27.59
Hyperlipidemia, %				< 0.0001
No	31.22	33.03	21.27
Yes	68.78	66.97	78.73
CVD, %				< 0.0001
No	91.59	93.63	80.35
Yes	8.41	6.37	19.65
Stroke, %				< 0.0001
No	97.16	97.98	92.66
Yes	2.84	2.02	7.34
MgDS, %				< 0.0001
Low MDS	79.78	82.45	65.06
Middle MDS	14.42	13.01	22.24
High MDS	5.79	4.54	12.70

OAB, overactive bladder; BMI, body mass index; PIR, poverty income ratio; MgDS, magnesium depletion score; CVD, cardiovascular disease.

Statistical analysis: continuous variables are expressed as mean ± standard error, while categorical variables are presented as weighted percentages. To compare groups, weighted linear regression analysis was used for continuous variables, and weighted chi-square tests were applied for categorical variables. Statistical significance was defined as a p-value less than 0.05.

Table 2 shows the distribution of MgDS categories. Participants with higher MgDS tended to be older, female, less educated, have lower PIR, be obese, and have a greater burden of chronic conditions. Notably, the prevalence of OAB increased progressively across MgDS categories, supporting a potential positive association between magnesium depletion and OAB.

Table 2.

Weighted characteristics of study participants by different MgDS group.

Characteristics	Low MgDS	Middle MgDS	High MgDS	P value
	22,383	4233	2005
Age, years	43.38 ± 0.23 a	60.01 ± 0.30 b	68.02 ± 0.35 c	< 0.0001
PIR	3.02 ± 0.03 a	3.28 ± 0.04 b	2.97 ± 0.06 c	< 0.0001
BMI, kg/m2	28.82 ± 0.09 a	29.81 ± 0.15 b	31.02 ± 0.22	< 0.0001
Age group, %				< 0.0001
< 40y	43.93	8.44	1.61
40–60y	39.61	38.44	20.04
≥ 60y	16.46	53.13	78.36
Gender, %				< 0.0001
Female	49.68	51.89	61.07
Male	50.32	48.11	38.93
Race, %				< 0.0001
Mexican American	9.11	3.17	2.36
Non-Hispanic White	66.85	81.16	82.20
Non-Hispanic Black	10.89	8.76	10.25
Other Hispanic	5.64	2.68	2.21
Other races	7.51	4.22	2.97
Marital status, %				0.08
Solitude	36.02	35.49	39.34
Cohabitation	63.98	64.51	60.66
Education, %				< 0.001
Less than high school	14.55	14.34	18.60
High school	22.98	23.27	26.07
Above high school	62.47	62.40	55.33
PIR, %				< 0.0001
< 1.3	21.13	15.66	19.36
1.3–3.5	35.42	34.66	41.21
> =3.5	43.45	49.68	39.42
BMI, %				< 0.0001
Normal (< 25 kg/m2)	31.73	23.02	17.62
Overweight (25–30 kg/m2)	32.19	35.33	33.18
Obese (≥ 30 kg/m2)	36.08	41.65	49.20
Smoke, %				< 0.0001
Never	56.25	49.88	47.77
Former	21.97	34.67	42.22
Current	21.78	15.45	10.01
Alcohol consumption, %				< 0.0001
Never	10.36	9.13	12.83
Former	12.19	15.66	22.52
Mild	36.12	41.07	38.54
Moderate	17.79	18.07	16.93
Heavy	23.54	16.06	9.19
Hypertension, %				< 0.0001
No	70.48	36.68	13.38
Yes	29.52	63.32	86.62
Diabetes, %				< 0.0001
No	81.61	67.56	54.08
Borderline	7.52	10.55	11.54
Yes	10.86	21.89	34.38
Hyperlipidemia, %				< 0.0001
No	35.15	17.98	10.13
Yes	64.85	82.02	89.87
CVD, %				< 0.0001
No	94.94	82.91	67.15
Yes	5.06	17.09	32.85
Stroke, %				< 0.0001
No	98.27	94.41	88.64
Yes	1.73	5.59	11.36
OAB, %				< 0.0001
No	87.49	76.34	66.37
Yes	12.51	23.66	33.63

MgDS, magnesium depletion score; BMI, Body mass index; PIR, Poverty income ratio; CVD, Cardiovascular Disease; OAB, Overactive bladder.

Statistical analysis: continuous variables are expressed as mean ± standard error, while categorical variables are presented as weighted percentages. To compare groups, weighted linear regression analysis was used for continuous variables, and weighted chi-square tests were applied for categorical variables. Statistical significance was defined as a P-value less than 0.05.

^aLow MgDS vs. Middle MgDS, P < 0.05; ^bMiddle MgDS vs. High MgDS, P < 0.05; ^cHigh MgDS vs. Low MgDS, P < 0.05.

Multivariate regression analysis

Table 3 summarizes the results of the weighted multivariable logistic regression analysis assessing the association between MgDS and OAB. In the unadjusted model (Model 1), each one-point increase in MgDS was strongly associated with higher odds of OAB (OR = 1.59, 95% CI 1.53–1.65, p < 0.0001). This association remained significant but was attenuated after adjusting for demographic and socioeconomic factors in Model 2 (OR = 1.16, 95% CI 1.10–1.22, p < 0.0001), and persisted in the fully adjusted model (Model 3), which also accounted for lifestyle factors and comorbidities (OR = 1.09, 95% CI 1.03–1.15, p = 0.002).

Table 3.

Weighted multivariable logistic regression results of MgDS with OAB.

MgDS	OR (95%CI)		OR (95%CI)		OR (95%CI)
	Model 1	P value	Model 3	P value	Model 3	P value
Continuous	1.59(1.53,1.65)	< 0.0001	1.16(1.10,1.22)	< 0.0001	1.09(1.03,1.15)	0.002
Categories
Low MgDS (0–1 point)	Ref		Ref		Ref
Middle MgDS (2 points)	2.17(1.95,2.41)	< 0.0001	1.28(1.13,1.44)	< 0.001	1.17(1.03,1.33)	0.02
High MgDS (3–5 points)	3.54(3.15,3.99)	< 0.0001	1.46(1.27,1.67)	< 0.0001	1.20(1.05,1.38)	0.01
P for trend	< 0.0001		< 0.0001		0.002

MgDS, magnesium depletion score; OAB, overactive bladder; PIR, poverty income ratio; BMI, body mass index; CVD, cardiovascular diseases; OR, odds ratio; 95% CI, 95% confidence interval.

Statistical analysis:

Model 1, no covariates were adjusted;

Model 2, adjusted for age, sex, race, marital status, educational level, PIR, BMI;

Model 3, adjusted for age, sex, race, marital status, educational level, PIR, BMI, smoking status, alcohol consumption, and history of diabetes, CVD, hypertension, hyperlipidemia, or stroke.

When MgDS was analyzed as a categorical variable, compared with the low MgDS group, participants in the middle and high MgDS groups had significantly higher odds of OAB in Model 3 (middle: OR = 1.17, 95% CI 1.03–1.33, p = 0.02; high: OR = 1.20, 95% CI 1.05–1.38, p = 0.01). A significant dose-response trend was observed (p for trend = 0.002).

These results indicate that higher MgDS is independently associated with increased OAB risk, even after adjusting for a broad range of potential confounders.

Stratified and interaction analysis

The subgroup analyses (Fig. 2; Table 4) showed that the positive association between MgDS and OAB was generally consistent across most subgroups, with no significant interactions for age, sex, race/ethnicity, education, marital status, income, BMI group, hypertension, or cardiovascular disease (all p for interaction > 0.05). Notably, a significant interaction was found for smoking status (p for interaction < 0.001), with a stronger association among never smokers but not among current smokers. In addition, the association appeared more pronounced in women, middle-aged adults, non-Hispanic White participants, individuals with lower socioeconomic status, and those who were obese, although these interactions were not statistically significant. These findings suggest that certain demographic and lifestyle factors may influence the relationship between magnesium depletion and OAB.

Fig. 2.

Forest plot of the association between MgDS (continuous) and OAB risk across different subgroups. Odds ratios (ORs) and 95% confidence intervals (CIs) were derived from fully adjusted logistic regression models (Model 3), adjusting for all covariates except for the stratifying variable in each respective subgroup.

Table 4.

Weighted subgroup analysis of the association between the different MgDS and OAB.

Characteristics	OR (95%CI)			P for trend	P for interaction
	Low	Middle	High
Age group					0.13
20–40 years	Ref	1.32(0.81,2.16)	0.96(0.28,3.33)	0.38
40–60 years	Ref	1.32(1.03,1.69)	1.52(1.10,2.10)	0.002
> 60 years	Ref	1.08(0.94,1.25)	1.18(1.02,1.36)	0.03
Gender					0.99
Female	Ref	1.29(1.11,1.50)	1.39(1.16,1.66)	< 0.0001
Male	Ref	1.02(0.86,1.22)	1.00(0.83,1.22)	0.86
Race					0.09
Mexican American	Ref	1.16(0.88,1.53)	1.19(0.69,2.06)	0.33
Other Hispanic	Ref	1.38(0.87,2.19)	1.13(0.65,1.95)	0.27
Non-Hispanic White	Ref	1.16(0.99,1.35)	1.23(1.04,1.45)	0.01
Non-Hispanic Black	Ref	1.02(0.84,1.25)	1.04(0.84,1.28)	0.7
Other races	Ref	1.79(1.05,3.05)	1.40(0.71,2.76)	0.04
Educational level					0.35
Less than high school	Ref	0.97(0.74,1.27)	1.05(0.81,1.35)	0.85
High school	Ref	1.34(1.06,1.69)	1.28(0.96,1.69)	0.02
Above high school	Ref	1.18(0.98,1.43)	1.23(0.96,1.57)	0.04
Marital status					0.64
Solitude	Ref	1.14(0.97,1.34)	1.29(1.06,1.58)	0.01
Cohabitation	Ref	1.19(0.99,1.42)	1.15(0.93,1.41)	0.06
PIR group					0.58
<1.3	Ref	1.19(0.99,1.43)	1.25(0.93,1.69)	0.04
1.3–3.5	Ref	1.30(1.10,1.54)	1.22(0.99,1.51)	0.01
> 3.5	Ref	1.06(0.83,1.35)	1.19(0.93,1.53)	0.24
BMI group					0.53
< 25 kg/m2	Ref	1.25(0.96,1.62)	0.88(0.61,1.28)	0.70
25–30 kg/m2	Ref	1.06(0.85,1.30)	1.20(0.93,1.55)	0.17
> 30 kg/m2	Ref	1.24(1.01,1.51)	1.35(1.11,1.64)	0.002
Smoking status					0.004
Never	Ref	1.22(1.00,1.48)	1.36(1.10,1.68)	0.004
Former	Ref	1.06(0.86,1.31)	1.16(0.93,1.45)	0.22
Now	Ref	1.15(0.86,1.55)	0.72(0.47,1.11)	0.69
History of hypertension					0.24
No	Ref	1.26(1.03,1.55)	1.22(0.83,1.81)	0.03
Yes	Ref	1.14(0.97,1.33)	1.22(1.04,1.43)	0.01
History of CVD					0.33
No	Ref	1.13(0.97,1.32)	1.26(1.03,1.54)	0.01
Yes	Ref	1.36(1.04,1.77)	1.23(0.92,1.64)	0.10

MgDS, magnesium depletion score; OAB, overactive bladder; BMI, body mass index; PIR, poverty income ratio; CVD, cardiovascular disease; OR, odds ratio; 95% CI, 95% confidence interval.

Statistical analysis: subgroup analyses were conducted in Model3 adjusting for age, sex, race, marital status, educational level, PIR, BMI, smoking status, alcohol consumption, and history of diabetes, CVD, hypertension, hyperlipidemia, or stroke, excepting the stratification variable itself.

Discussion

This large, nationally representative study identified a significant association between MgDS and OAB in U.S. adults. Higher MgDS was independently linked to an increased risk of OAB, even after adjusting for demographic, lifestyle, and clinical confounders. This correlation was particularly pronounced in individuals with elevated MgDS (≥ 3 points). The association remained consistent across different analytical models, supporting the potential role of magnesium depletion in OAB pathophysiology. This supports the hypothesis that chronic magnesium depletion, as captured by MgDS, may reflect underlying neuromuscular or inflammatory imbalances contributing to OAB. Given that MgDS integrates multiple clinical factors (e.g., renal function, medication use), it may reflect an epidemiologic risk profile for OAB.

Previous studies have reported associations between low magnesium intake or serum magnesium levels and urinary symptoms such as urgency, nocturia, and increased frequency. For example, a study found that urinary magnesium as a potential marker for risk of acute urinary retention²⁵. Similarly, a Japanese cohort study observed that dietary magnesium intake was inversely associated with nocturia severity²⁶. However, these studies primarily relied on dietary recall or serum magnesium, both of which have notable limitations. Serum magnesium often remains within the normal range even in the presence of intracellular deficiency, and dietary data are prone to recall bias and short-term variability. These differences may partly reflect variations in study populations. Unlike our nationally representative U.S. adult sample with diverse ethnic groups, previous studies were conducted in specific regional cohorts with narrower age ranges or different baseline health conditions, which may affect generalizability. In contrast, our study uses the MgDS, which integrates multiple clinical indicators such as renal function and medication use, offering a more comprehensive reflection of chronic magnesium status. This may explain why our findings demonstrate a stronger and more consistent association with OAB. To our knowledge, this is the first population-based study to explore the relationship between clinically-integrated magnesium depletion risk and OAB symptoms in a nationally representative sample.

Several biological mechanisms may explain the observed association between MgDS and OAB. Magnesium plays a vital role in smooth muscle relaxation and neuromuscular regulation, primarily through its function as a natural calcium antagonist²⁷. In the bladder, intracellular calcium levels regulate detrusor muscle contractions. Magnesium deficiency can lead to excess calcium influx, causing increased smooth muscle excitability and involuntary detrusor contractions, which are characteristic of OAB²⁸. An early study found that magnesium treatment may have a positive effect on urinary frequency, urgency, and voiding difficulty²⁹. Another potential pathway involves oxidative stress and chronic inflammation, which are widely implicated in the pathogenesis of OAB. Magnesium is well known for its anti-inflammatory and antioxidant properties, and magnesium deficiency has been shown to induce inflammatory responses, including the release of C-reactive protein (CRP) in animal models³⁰. However, findings from human studies, including both randomized trials³¹ and observational studies^32–34, have been inconsistent regarding the effects of magnesium on serum CRP levels. Beyond CRP, magnesium deficiency has also been associated with increased production of pro-inflammatory cytokines, such as tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6)^35,36. Multiple studies have reported a strong correlation between inflammation and the onset and progression of OAB. Prolonged inflammation can induce structural and functional changes in the bladder, leading to increased sensitivity and exaggerated bladder responses, thereby contributing to the development of OAB symptoms^8,37,38. Additionally, molecular imbalances in inflammatory proteins may further promote OAB progression³⁹. Tyagi et al.⁴⁰ demonstrated that patients with OAB exhibit elevated urinary levels of monocyte chemoattractant protein-1 (MCP-1), soluble CD40 ligand (sCD40L), growth-regulated oncogene-alpha (GRO-α), macrophage inflammatory protein-1 beta (MIP-1β), IL-5, IL-12p70/p40, and epidermal growth factor (EGF). These findings suggest neutrophil, eosinophil, and mast cell infiltration in the bladder of OAB patients. Furthermore, studies have shown that mast cells, T lymphocytes, and B lymphocytes are increased in both number and activity in the detrusor muscle of OAB patients^41–43, reinforcing the role of immune activation in disease progression. Given that inflammation is increasingly recognized as a key factor in OAB development, the biological plausibility of linking MgDS with OAB risk through inflammatory pathways is well supported. These findings highlight the potential importance of magnesium status in bladder health and suggest that addressing magnesium depletion may be relevant for OAB prevention and management.

Metabolic factors may also play a role in this relationship. Magnesium depletion is frequently observed in individuals with diabetes, hypertension, and metabolic syndrome^19,20,44, all of which are known risk factors for OAB. Given that MgDS incorporates multiple determinants of magnesium status—including renal function, diuretic and PPI use, and alcohol consumption—it provides a more comprehensive assessment of long-term magnesium depletion than serum magnesium alone. This may explain why individuals with higher MgDS scores exhibited a stronger association with OAB, as they likely have chronic magnesium insufficiency compounded by underlying metabolic dysfunction. Moreover, the components of the MgDS—such as diuretic use, renal dysfunction, and chronic alcohol consumption—are all associated with systemic inflammation, oxidative stress, and autonomic dysregulation, which may exacerbate bladder dysfunction⁴⁵. For example, inflammation can sensitize afferent neurons and disrupt the urothelial barrier, further contributing to urgency symptoms. As such, the MgDS may reflect both magnesium-dependent physiological dysregulation and broader systemic disturbances that influence bladder function. This multifaceted interplay between electrolyte imbalance, inflammation, and neuromuscular dysfunction provides a plausible biological framework linking higher MgDS to elevated OAB risk. However, given our cross-sectional design, the causal relationship among magnesium depletion, metabolic syndrome, systemic inflammation, and OAB cannot be established and remains hypothetical. Prospective cohort studies and experimental research are needed to confirm these pathways.

The subgroup analysis further reinforces the association between MgDS and OAB, while also highlighting potential effect modifiers. Notably, sex differences were observed, with a significant association in females, whereas no significant relationship was found in males. This finding is consistent with the higher prevalence of OAB in women, which may be influenced by hormonal fluctuations, pelvic floor dysfunction, and differences in bladder innervation⁴⁶. In women, the association between MgDS and OAB may be influenced by menopausal status. Estrogen plays a key role in maintaining urothelial integrity, detrusor function, and pelvic floor support. Estrogen plays a key role in maintaining urothelial integrity and detrusor muscle function, and declining estrogen levels—particularly after menopause—may exacerbate the effects of magnesium depletion on bladder hyperactivity⁴⁷. Additionally, prior studies have suggested that women may be more susceptible to inflammation-related bladder dysfunction, which aligns with the known anti-inflammatory role of magnesium. Although NHANES does not consistently capture menopausal status, future studies should consider stratifying by menopause or assessing hormone replacement therapy use to clarify this relationship.

Another notable interaction was observed with smoking status, where the association between MgDS and OAB was stronger in never smokers but not significant in current smokers. One potential explanation is that smoking itself induces oxidative stress and inflammation, which are also pathways affected by magnesium depletion^48,49. This overlapping mechanism may mask or dilute the effect of MgDS in smokers due to a “ceiling effect.” Moreover, smokers may have baseline magnesium depletion due to higher urinary excretion and impaired intestinal absorption⁵⁰, minimizing exposure variation within the group. Future mechanistic studies are warranted to explore how lifestyle factors like smoking interact with micronutrient status in modulating bladder dysfunction. However, the subgroup and interaction analyses were exploratory and should be interpreted with caution. Given the number of comparisons performed and the absence of formal correction for multiple testing, some associations may reflect chance findings. Additionally, the sample sizes within certain subgroups may have limited the statistical power to detect or confirm true effect modification. Future studies with targeted designs and prespecified hypotheses are needed to validate these interactions.

From a clinical perspective, MgDS may serve as a practical risk stratification tool to guide early identification of individuals at risk for overactive bladder. For example, in older adults taking diuretics or PPIs, a high MgDS could prompt clinicians to assess urinary symptoms more proactively or consider lifestyle and dietary magnesium interventions. Additionally, in primary care or geriatric clinics, MgDS could be used as part of a broader metabolic risk profile to flag patients who may benefit from dietary counseling or laboratory testing to evaluate magnesium status more precisely. Importantly, MgDS relies on routinely available clinical variables—such as medication use, renal function, and alcohol consumption—making it a cost-effective and easily integrated tool in electronic health records. Although the effect sizes observed (e.g., OR = 1.20 for high vs. low MgDS) are modest, they are consistent with many other epidemiological associations involving micronutrient imbalances and chronic conditions. In the context of OAB—a common and often under-recognized syndrome—even small risk increases can have significant population-level impact. Moreover, magnesium deficiency is potentially reversible, suggesting that even modest risk reductions could translate into meaningful clinical benefit if confirmed by intervention studies.

This study had several limitations. This study has several methodological limitations that warrant consideration. First, due to its cross-sectional design, the observed association between MgDS and OAB cannot establish temporality or causality. Although we hypothesize that neuromuscular dysfunction, oxidative stress, and inflammation may mediate this relationship, prospective longitudinal studies are needed to confirm causal pathways and assess the predictive value of MgDS over time. Second, cross-sectional studies are inherently subject to missing data issues. While we minimized this limitation by performing multiple imputations for missing covariate data, residual bias cannot be ruled out. Third, OAB diagnosis in NHANES was based on self-reported symptoms using the OABSS, which may be subject to recall bias and misclassification. Fourth, MgDS was used as a proxy index for magnesium depletion. While it incorporates clinically relevant components, it does not directly measure serum or intracellular magnesium levels. Future research should validate MgDS against biochemical magnesium markers and explore its longitudinal association with both magnesium status and urologic outcomes. As diuretic use is a core component of MgDS and was not adjusted for separately in our models, it is possible that some of the observed association reflects medication-related bladder effects rather than magnesium depletion alone. This limitation should be addressed in future studies using more direct magnesium biomarkers and component-specific models. Additionally, although NHANES uses a complex, multistage probability sampling design, making the results generalizable to the U.S. adult population, the applicability to other geographic regions and racial/ethnic groups requires further validation. Moreover, our models did not include dietary magnesium intake, which is a direct determinant of magnesium status. Although NHANES collects 24-hour recall data, these values often vary across cycles and are prone to recall bias and non-differential misclassification, leading to their exclusion in our primary analysis. Nevertheless, the lack of this variable may result in residual confounding and should be addressed in future studies with more robust dietary data. In addition, certain covariates included in our fully adjusted model—such as hypertension, diabetes, and CVD—may be downstream consequences of magnesium depletion. Their inclusion may therefore constitute overadjustment, potentially underestimating the strength of the true association. Future causal modeling or mediation analyses may help clarify these interrelationships and identify which factors should be considered confounders versus intermediates. Finally, despite adjusting for multiple potential confounders, unmeasured factors such as genetics, lifestyle, and environmental influences may have contributed to residual confounding.

While our findings suggest that MgDS is associated with OAB risk, it should be interpreted as a proxy measure rather than a definitive diagnostic tool. Future research should focus on several key areas. First, validating MgDS against direct magnesium biomarkers (e.g., serum or erythrocyte magnesium) in clinical cohorts would strengthen its utility as a surrogate index. Second, prospective longitudinal studies are needed to determine whether high MgDS predicts the development or progression of OAB over time. Third, intervention trials could assess whether magnesium supplementation improves OAB symptoms in individuals with high MgDS, helping to clarify potential therapeutic pathways.

Conclusion

In this nationally representative study, we found a significant association between MgDS and OAB in U.S. adults. This association remained robust after adjusting for multiple confounders, suggesting that magnesium depletion may contribute to OAB pathophysiology. However, given the cross-sectional design, further prospective and interventional studies are needed to determine whether improving magnesium status could effectively prevent or manage OAB symptoms.

Supplementary Information

Below is the link to the electronic supplementary material.

Author contributions

H.B., and K.L.: Conceptualization, Methodology, Writing—Original Draft, Funding Acquisition; Y.Z., and K.L.: Data Curation, Formal Analysis, Visualization; H.B., Y.Z. and K.L.: Investigation, Validation, Writing—Review & Editing; K.L.: Project Administration, Resources, Supervision; All authors have read and agreed to the published version of the manuscript.

Data availability

The datasets generated and/or analyzed during the current study are publicly available in the National Health and Nutrition Examination Survey (NHANES) repository, accessible at https://www.cdc.gov/nchs/nhanes/. All results supporting this research are fully presented in the figures and tables within this manuscript. Additional detailed data and processing code are available upon reasonable request from the corresponding author.

Declarations

Competing interests

The authors declare no competing interests.

Ethical approval

The study was conducted in accordance with the Declaration of Helsinki and approved by the National Center for Health Statistics Ethics Review Board (Protocol #2011-07 and Continuation of Protocol #2011-07). Informed consent was obtained from all participants involved in the study.