Introduction
Calcium metabolism and excretion play a crucial role in human health. As a micromineral, calcium is essential for many physiological processes, and alterations in serum calcium levels (hypocalcemia or hypercalcemia) can have serious health consequences. Complex regulatory systems, including calcium-sensing receptors and hormones such as parathyroid hormone (PTH) and vitamin D [
1], work together to maintain calcium balance [
2]. This balance between absorbed calcium, secreted calcium, and serum calcium is achieved through interactions among calcitonin, 1,25-dihydroxycholecalciferol, PTH, and ionized calcium. Glomerular filtration of albumin-free plasma calcium, along with substantial calcium reabsorption along different tubular segments, produces urinary calcium. Urinary calcium excretion is influenced by multiple calciuric factors, including 1,25(OH)₂D, PTH, sex hormones, and dietary intake [
3]. Thus, excessive intestinal absorption or increased bone resorption may overload the glomerulus, while tubular dysfunction and reduced reabsorption can result in elevated urinary calcium excretion, or hypercalciuria.
Hypercalciuria, defined as excessive urinary calcium excretion, is a significant health concern most commonly linked to kidney stones and osteoporosis. Its occurrence worldwide is influenced by geographical location, diet, and heredity. Approximately 5% to 10% of the general population is estimated to have hypercalciuria, with idiopathic hypercalciuria being the most common type, particularly among individuals with calcium oxalate nephrolithiasis and osteoporosis [
4]. Hypercalciuria is especially prevalent in developed countries, where dietary practices increase the risk of kidney stones and osteoporosis [
5]. In India, the prevalence of hypercalciuria among children was reported at 6.5% [
6]. However, its prevalence among the adult Indian population remains inadequately studied. While relatively few studies on hypercalciuria exist, several have reported no significant sex differences in urinary calcium excretion [
6–
8].
Numerous studies have explored the association of hypercalciuria with kidney stone formation [
9] and osteoporosis [
10]. However, the relationship between serum calcium status (hypocalcemia or hypercalcemia) and urinary calcium excretion (hypocalciuria or hypercalciuria) has received less attention. Moreover, the association of demographic variables with hypercalciuria has not been thoroughly examined in Northeast India, particularly in Manipur. Considering these gaps and the importance of the issue, this study sought to investigate the association of demographic variables and serum calcium with hypercalciuria among Meitei adults in Manipur, Northeast India.
Materials and Methods
Study Design and Setting
This cross-sectional study was conducted in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for observational research. Participants were recruited between June 2023 and December 2023 from Meitei communities residing in the 5 valley districts of Manipur: Imphal-East, Imphal-West, Bishnupur, Thoubal, and Kakching (
Figure 1).
Study Population and Sampling
The study population comprised adults of Meitei ethnicity, aged 19 to 60 years, who were permanent residents of the 5 valley districts of Manipur (Imphal-East, Imphal-West, Bishnupur, Thoubal, and Kakching). Pregnant women were excluded to avoid confounding from pregnancy-related changes and calcium supplementation. Other individuals reporting current use of calcium supplements were also excluded, as supplementation could alter serum and urinary calcium levels.
The required sample size was estimated using Epi Info software, assuming a 95% confidence level, 50% expected frequency, and a 5% margin of error, yielding a target of 663 participants. Eligible individuals were identified through a multistage random sampling process involving the selection of constituencies, polling stations, and households. In the first stage, 19 constituencies were randomly selected across the 5 districts. In the second stage, 20 polling stations were chosen to represent specific localities. In the final stage, households within the selected polling stations were surveyed, and eligible individuals were identified according to the inclusion criteria (
Figure 2).
A total of 663 individuals were approached through household visits. Of these, 487 consented and were screened for eligibility; 465 met the inclusion criteria, and 423 completed all required assessments, including serum and random urine sample collection. Ten participants were excluded due to incomplete biological samples. Thus, the final analysis comprised 413 participants (272 females and 141 males). Reasons for non-participation included refusal (n=22), failure to meet inclusion criteria (n=42), and incomplete data collection (n=10).
Data Collection and Study Variables
Demographic data such as age, sex, and district of residence were collected using a structured questionnaire. Clinical data were obtained through blood and random urine samples. Serum and urine calcium and creatinine levels were considered predictor variables, along with age. Age was categorized into 2 groups: ≤40 years and >40 years, based on the mean age at which the peak prevalence of hypercalciuria is expected.
The primary outcome was hypercalciuria, defined using the random urinary calcium-to-creatinine ratio, with interpretation as follows: <0.14 considered normal, >0.20 indicating hypercalciuria [
11]. Values between 0.14 and 0.20 were classified as borderline and labeled as the “at-risk” group. Serum calcium levels were categorized as hypocalcemia (<8.5 mg/dL), normocalcemia (8.5–10.5 mg/dL), and hypercalcemia (>10.5 mg/dL) [
12], enabling assessment of their relationship with urinary calcium excretion.
Specimen Collection and Laboratory Analysis
Approximately 2 mL of venous blood was collected in non-ethylenediaminetetraacetic acid coated microcentrifuge tubes. Random spot urine samples were collected on the same day in sterile containers, using the clean-catch midstream method to minimize contamination [
13]. All samples were collected during household visits and processed in community settings according to the survey schedule. Collected specimens were refrigerated at 4°C until analysis. Serum and urine creatinine levels were measured using Jaffe’s reaction method [
14]. Urine samples were diluted with distilled water at a 1:20 ratio, and results were multiplied by 20. Serum and urine calcium levels were measured using the Arsenazo III method [
15]. For urine calcium measurement, samples were diluted with distilled water at a 1:2 ratio, and the pH was adjusted to 3–4 by adding drops of 0.1 mol/L HCl; the final result was multiplied by 3. All measurements were performed using an automated biochemistry analyzer, the Erba Chem 5x (Erba), following standard operating procedures. Internal quality control checks were run before each batch of samples to ensure accuracy and reproducibility.
Statistical Methods
Statistical analyses were conducted using IBM SPSS Statistics for Windows ver. 21.0 (IBM Corp.). Data were expressed as mean±standard deviation (SD) with 95% confidence intervals (CIs), as well as frequency and percentage. The significance of differences among the hypercalciuria, at-risk, and normal groups was assessed using analysis of variance (ANOVA) for serum creatinine, serum calcium, and random urine calcium and creatinine levels. Tukey’s post hoc test was applied to evaluate differences between group pairs (hypercalciuria vs. at-risk, hypercalciuria vs. normal, and at-risk vs. normal). The chi-square test was used to examine differences in demographic variables and serum calcium status among the 3 groups. The association of urinary calcium-to-creatinine status with demographic variables and serum calcium status was analyzed using a multinomial logistic regression model. Urinary calcium-to-creatinine status was the dependent variable, with demographic variables and serum calcium status entered as covariates of interest. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the predictive power of serum and urine calcium for hypercalciuria. The cut-off values for these parameters were determined using the maximum Youden index [
16]. A
p-value <0.05 was considered statistically significant.
Ethics Statement
The study was reviewed and approved by the Institutional Human Ethical Committee (IHEC) of Manipur University under reference number MU/IHEC/2020/018, with approval granted on December 14, 2020. The IHEC confirmed the use of informed consent, and all participants provided written informed consent prior to enrollment.
Results
Descriptive Data of General Clinical Characteristics of Participants
Table 1 presents the general characteristics of the study participants. Hypercalciuria was significantly more prevalent in the 41–60-year age group (66.2%) compared with the younger 19–40-year group (33.8%), providing strong evidence of an age-related association. By sex, females had a higher prevalence of hypercalciuria (75.3%) than males (24.7%). District-level variation was also observed, with Kakching and Imphal-West reporting the highest prevalence among the hypercalciuric group (28.6%) and Imphal-East the lowest (7.8%). With respect to serum calcium status, hypercalciuria prevalence was highest in normocalcemia (53.2%) and hypercalcemia (33.8%), and lowest in hypocalcemia (13.0%). No significant association was observed between hypercalciuria and either serum creatinine or serum calcium levels. For urine creatinine, the lowest mean value was found in the hypercalciuric group (4.67 mg/dL), while the highest was observed in the normal group (9.87 mg/dL). Urinary calcium was highest in the hypercalciuric group (8.55 mg/dL) and lowest in the normal group (4.93 mg/dL).
Serum and urine calcium and creatinine levels by sex
Table 2 shows sex-specific mean±SD values of serum and urine calcium and creatinine. Overall, 18.64% of participants had hypercalciuria, 23.49% were at risk, and 57.87% were within the normal range. The mean±SD of serum creatinine was slightly higher in the risk group (0.93±0.20 mg/dL), followed by the normal group (0.92±0.22 mg/dL) and the hypercalciuric group (0.90±0.22 mg/dL). The mean serum calcium level was marginally higher in the hypercalciuric group (10.07±1.35 mg/dL), followed by the normal group (10.06±0.88 mg/dL) and the risk group (9.92±1.13 mg/dL). However, 1-way ANOVA indicated no statistically significant differences among the groups for serum creatinine or serum calcium. In contrast, significant differences were found in urinary parameters. Random urine creatinine increased progressively from the hypercalciuric group (4.67±2.69 mg/dL) to the risk group (7.18±3.57 mg/dL) and was highest in the normal group (9.87±5.15 mg/dL). Significant differences were observed among all group pairs (
p<0.001). Conversely, urinary calcium exhibited a declining trend: highest in the hypercalciuric group (8.55±4.15 mg/dL), slightly lower in the risk group (7.67±3.71 mg/dL), and lowest in the normal group (4.93±3.07 mg/dL). The association across groups was statistically significant (
p<0.001), with differences noted between hypercalciuria vs. normal and risk vs. normal, though not between hypercalciuria and risk. These patterns were consistent across both sexes, although certain variations were noted. Males had higher mean serum creatinine and urine creatinine values, whereas females had higher mean calcium levels in both the hypercalciuric and risk groups.
Urinary calcium excretion by demographic and serum calcium levels
Table 3 summarizes the association of urinary calcium excretion with demographic variables and serum calcium status. A significant relationship between age and urinary calcium excretion was observed (
p<0.001), indicating that older individuals were more likely to be hypercalciuric. Within the hypercalciuric group, 66.2% were aged 41–60 years, compared with 33.8% in the 19–40 group. Similarly, in the risk group, 53.6% were in the 41–60 group versus 46.4% in the 19–40 group. In contrast, among the normal group, the majority (61.9%) were younger (19–40 years), while 38.1% were in the 41–60 group. Serum calcium status was also significantly associated with urinary calcium excretion (
p<0.05). Among the hypercalciuric group, 13.0% were hypocalcemic, 33.8% hypercalcemic, and 53.2% normocalcemic. In the risk group, 7.2% were hypocalcemic, 16.5% hypercalcemia, and 76.3% normocalcemic. In contrast, among individuals with normal urinary calcium excretion, 74.5% were normocalcemic, 21.3% hypercalcemic, and 4.2% hypocalcemic. Sex differences were also noted: among females, 75.3% were hypercalciuric, 67.0% at risk, and 62.3% normal. Among males, 24.7% were hypercalciuric, 33.0% at risk, and 37.7% normal. However, no statistically significant association was found between sex and urinary calcium status.
Odds of Hypercalciuria by Demographics and Serum Calcium Levels
Table 4 displays the odds ratios (ORs) for hypercalciuria relative to demographic variables and serum calcium status, using normal urinary calcium as the reference. Females had 1.4-fold higher odds (OR, 1.43; 95% CI, 0.77–2.63;
p=0.26) of developing hypercalciuria compared with males. Individuals aged 41–60 years had a threefold higher risk (OR, 3.19; 95% CI, 1.86–5.47;
p<0.001) compared with those aged 19–29 years. District-wise analysis showed significant associations. Compared with Imphal-East, individuals from Imphal-West had 5.77-fold higher odds (OR, 5.77; 95% CI, 2.18–15.28;
p<0.001), Kakching 9.69-fold higher odds (OR, 9.69; 95% CI, 3.55–26.39;
p<0.001), and Bishnupur 3.90-fold higher odds (OR, 3.90; 95% CI, 1.46–10.39;
p=0.006). Thoubal showed no significant difference, although its OR was 3.28 (95% CI, 1.05–10.28;
p=0.41). Comparing calcium status, hypocalcemic individuals had 3.5-fold higher odds of hypercalciuria (OR, 3.52; 95% CI, 1.33–9.31;
p=0.01) relative to normocalcemic individuals. Hypercalcemic individuals also had significantly higher odds (OR, 2.10; 95% CI, 1.15–3.84;
p=0.02). In the at-risk category, females had slightly higher odds (OR, 1.11; 95% CI, 0.66–1.85;
p=0.69) compared with males. Participants aged 41–60 years had 1.8-fold higher odds (OR, 1.88; 95% CI, 1.16–3.02;
p=0.01) compared with those aged 19–29 years. District-wise associations in the risk group were also significant: Imphal-West (OR, 3.63; 95% CI, 1.72–7.65;
p=0.001), Kakching (OR, 3.25; 95% CI, 1.38–7.62;
p=0.001), and Bishnupur (OR, 2.65; 95% CI, 1.26–5.57;
p=0.01). Thoubal showed no significant association (OR, 1.89; 95% CI, 0.75–4.79;
p=0.17). Individuals with hypocalcemia had 1.5-fold higher odds of being in the risk category (OR, 1.52; 95% CI, 0.55–4.20;
p=0.41), while those with hypercalcemia had lower odds (OR, 0.73; 95% CI, 0.39–1.38;
p=0.03) compared with normocalcemic individuals.
ROC Curve Analysis
Table 5 summarizes the ROC curve analysis, evaluating the predictive utility of serum and urine calcium for hypercalciuria. Urinary calcium had an area under the ROC curve (AUC) of 0.70, with a predictive cut-off value of 23.07 mg/dL, sensitivity of 58.40%, and specificity of 75%. In contrast, serum calcium had a much lower predictive value, with an AUC of 0.52.
Discussion
Key Results
This study is among the few conducted to investigate the prevalence of hypercalciuria in Manipur. We assessed its frequency among Meitei adults aged 19 to 60 years residing in the valley districts. Globally, hypercalciuria affects 5% to 10% of adults and occurs in approximately one-third of individuals with calcium stones [
17]. Idiopathic hypercalciuria accounts for about 40% to 50% of recurrent calcium stone cases [
18]. In our study, the prevalence of hypercalciuria was 75.3% among females and 24.7% among males, yielding an overall prevalence of 18.64%, which is higher than the global average.
Hypercalciuria is well recognized as a major risk factor for kidney stone formation. The prevalence of kidney stone disease in Manipur is notably high. Marak et al. [
19] reported a prevalence rate of 22.4%, whereas Konjengbam et al. [
20] reported a slightly lower rate of 11.24%. This high prevalence of kidney stones in Manipur may be partly explained by the elevated incidence of hypercalciuria observed in this population. Beyond stone formation, hypercalciuria also poses broader health risks, including urinary tract infections and reductions in bone mineral density, leading to osteopenia or osteoporosis.
In this study, random urine samples were used, with calcium levels expressed relative to creatinine. A low urine creatinine combined with relatively high urine calcium can result in a proportionally elevated calcium excretion, potentially reflecting factors such as reduced muscle mass or impaired renal function [
21]. Our findings showed low urine creatinine levels with high urine calcium, yielding elevated calcium-to-creatinine ratios. This observation is consistent with other studies, which have also reported that individuals with low creatinine and high calcium levels demonstrate increased calcium-to-creatinine ratios, indicative of hypercalciuria [
22].
Age emerged as a significant factor influencing hypercalciuria prevalence. Previous studies have demonstrated age-related variations, with hypercalciuria being common in children and adolescents. For example, a study reported that hypercalciuria is frequent among children aged 2 to 16 years, with younger children more likely to develop the disorder [
23]. Another study noted that 39% of healthy adolescents exhibit hypercalciuria [
24]. In contrast, our study showed that older adults were more susceptible. Participants aged 41 to 60 years had 3.19-fold higher odds of hypercalciuria compared with those aged 19 to 40 years. Similar findings have been reported in older adults, particularly postmenopausal women, who often take calcium supplements for osteoporosis prevention or treatment. Excess absorbed calcium may subsequently be excreted in the urine, contributing to hypercalciuria [
25]. Reports indicate that up to 40% of postmenopausal women exhibit high urinary calcium levels [
26]. Another study found elevated urinary calcium in 19% of postmenopausal women, further supporting a high prevalence in this subgroup [
27]. In older men, elevated urinary calcium may be influenced by diet, bone mineral density, and underlying medical conditions. Notably, higher urinary calcium excretion in older men has been linked to reduced trabecular bone mineral density, potentially leading to bone loss [
10]. Additionally, urinary sodium excretion has been correlated with calcium excretion, suggesting that dietary salt intake may influence calcium homeostasis [
28]. However, metabolic, developmental, and hereditary factors must also be considered to fully explain the association between age and hypercalciuria. Several studies have reported that calcium absorption, vitamin D levels, and nephrolithiasis risk increase around mid-adulthood (approximately 40 years), which may indirectly contribute to hypercalciuria [
29,
30].
Sex-related differences in hypercalciuria have also been reported. Golovanov et al. [
31] observed that men typically excrete more urinary calcium and exhibit a higher likelihood of oxalate stone formation, whereas women excrete less calcium overall, regardless of lithogenic factors. By contrast, our study found that women were more likely to have hypercalciuria, although the association was not statistically significant. Within the hypercalciuric group, females had 1.4 times greater odds than males, and within the at-risk group, females had 1.1 times greater odds. Women also exhibited higher urinary calcium excretion, often accompanied by lower creatinine excretion. These findings are consistent with previous reports suggesting that postmenopausal women are more prone to elevated urinary calcium [
27]. Men, in contrast, generally excrete less calcium but significantly higher amounts of creatinine, which may reduce their apparent susceptibility to hypercalciuria [
6,
8]. This sex-specific pattern may be partly explained by differences in renal calcium handling: women demonstrate reduced distal calcium reabsorption [
32], while men exhibit diminished proximal tubular calcium reabsorption.
Individuals with increased urinary calcium excretion in the absence of serum calcium abnormalities or identifiable disorders are generally classified as having idiopathic hypercalciuria [
33]. In our study, 53.2% of participants were normocalcemic with hypercalciuria, while the risk of hypercalciuria among normocalcemic individuals was 76.3%. Elevated urinary calcium load in such cases may result from increased intestinal absorption of calcium, reduced renal calcium reabsorption, and a tendency toward bone calcium loss [
34]. Nevertheless, hypercalciuria remains a complex polygenic trait in which diet plays a major role, and it may also result from heightened vitamin D responsiveness. In our study, 13.0% of participants exhibited hypocalcemic hypercalciuria, with a 3.5-fold higher odds of hypercalciuria. Tsuji et al. [
35] reported that hypocalcemia with hypercalciuria can arise from autosomal dominant hypocalcemia (ADH) caused by functional mutations in calcium-sensing receptors. In such cases, vitamin D deficiency may mask the typical hypercalciuria associated with ADH. Other studies have also linked hypocalcemia with hypercalciuria to genetic mutations affecting calcium-sensing mechanisms and related pathways [
36,
37]. Our findings indicate that hypocalcemia is statistically associated with increased odds of hypercalciuria, though this does not establish a direct causal relationship between low serum calcium and elevated urinary calcium excretion. The observed association could instead reflect common factors such as vitamin D deficiency, malnutrition, or hormonal disturbances that alter calcium balance. While rare genetic syndromes may contribute, they are unlikely to account for most cases in this population. Given the cross-sectional design of our study, serum and urinary calcium values were measured at a single time point, so some participants may have been misclassified due to transient fluctuations in calcium levels. Thus, our findings should be interpreted as associative rather than causal, and further studies are warranted to elucidate underlying mechanisms. Hypercalcemia with hypercalciuria represents another important clinical condition, with each disorder potentially influencing the other depending on genetic, metabolic, and therapeutic factors. In our study, 33.8% of participants had hypercalcemia with hypercalciuria, and individuals with hypercalcemia were 2.1 times more likely to develop hypercalciuria compared with normocalcemic individuals. According to Auron and Alon [
38], hypercalcemia with hypercalciuria often reflects disruptions in mineral homeostasis and may lead to acute kidney injury and renal calcifications. Jacobs et al. [
39] reported that impaired inactivation of vitamin D metabolites, due to CYP24A1 mutations, increases calcium absorption and can cause concurrent hypercalcemia and hypercalciuria. Although these 2 conditions frequently coexist, they may also occur independently, underscoring the need for individualized assessment and treatment strategies. Our analysis also revealed notable geographic differences in hypercalciuria prevalence across the valley districts. Significant associations were observed in Imphal-West, Bishnupur, and Kakching, with Kakching showing the highest odds (9.69) compared to other districts. Although our study did not examine contextual factors such as diet, environmental exposures, or healthcare access, these may contribute to the observed regional variation. Larger multi-district studies incorporating these variables are needed to clarify the drivers of such differences.
Regarding predictive analysis, AUC values greater than 0.9 indicate high accuracy, values between 0.7 and 0.9 indicate moderate accuracy, and values between 0.5 and 0.7 suggest low accuracy [
40]. In this study, urinary calcium excretion demonstrated moderate predictive ability for hypercalciuria (AUC, 0.70;
p<0.001). The predictive cut-off value of urinary calcium was 23.07 mg/dL, with 58.40% sensitivity and 75% specificity, both within acceptable ranges [
41]. By contrast, a prior study reported a lower cut-off of 10.15 mg/dL for urinary calcium to define hypercalciuria [
42]. While hypercalciuria may also result from elevated serum calcium leading to increased urinary excretion, our findings suggest that serum calcium alone does not reliably predict hypercalciuria, although it remains a useful marker of overall calcium homeostasis.
Strengths and Limitations of the Study
This investigation has both strengths and limitations. A key strength is that it is one of the few studies to examine hypercalciuria prevalence in Manipur, providing novel data on the frequency and risk of hypercalciuria using random urinary calcium-to-creatinine ratios among Meitei adults aged 19–60 years. The study demonstrated significant associations with age group and serum calcium status. However, limitations must be acknowledged. Factors such as environmental influences, dietary patterns, and detailed nutritional assessment were not measured, and these may affect calcium levels. Additionally, reliance on random urine samples rather than 24-hour urine collections may have introduced variability. The absence of food intake data is another limitation.
, Malvika Yumnam1
