ABSTRACT
Introduction:
Vitamin D and vitamin B12 deficiencies are major public health problems in many populations. Studies report a deficiency in the range of 20–80% of both micronutrients. Hence, a comparative study was conducted among a rural and an urban population to see the prevalence and factors associated with their deficiency.
Methodology:
The institutional ethics committee approved the study. Informed consent was taken from all the participants. Cross-sectional comparative analytical study among participants of rural and urban field practice areas of a medical college was undertaken. Measurements were made on 121 participants, 67 from urban areas, and 54 from rural regions. Participants were selected in a simple random sampling technique. Blood samples were collected in a standardized technique following aseptic conditions and transported to the laboratory maintaining a cold chain for analysis. Data were entered into Microsoft Excel and analyzed using Jamovi v2.4.11. Chi-square test, t-tests, and Mann-Whitney U tests were used, and tests of significance with P < 0.05 cut-off for rejecting the null hypothesis.
Results:
Apart from education, body mass index (BMI), and socioeconomic status, all factors were similar among rural and urban participants. The mean BMI of urban participants was more than rural counterparts. Deficiency of vitamin B12 was 52.2% in urban and 64.8% in rural areas; deficiency of vitamin D was 34.3% in urban and 13% in the rural sample. Mean values of vitamin D and vitamin B12 were significantly different, 17.77 ng/mL vis-a-vis 19.02 ng/mL and 254.82 pg/mL vis-a-vis 185.48 pg/mL, respectively, for urban and rural participants. Vitamin D was more deficient in urban areas, and vitamin B12 was more deficient in rural areas.
Conclusion:
Both deficiencies found in the participants are of concern and require different interventions. Urban participants should be advised more of outdoor activities, and rural participants should be educated more on dietary interventions. Supplements at the individual level may be advised as needed.
Keywords: Nutrition and metabolism, public health planning, urban and rural disparities, vitamin B12 deficiency, vitamin D3 deficiency
Introduction
Vitamin B12 is an important vitamin that keeps our nerve cells healthy and helps make DNA and RNA, which are the body’s genetic materials.[1] Vitamin B12 works closely with vitamin B9 to make red blood cells and help iron work better in the body.[2] Vitamin B12 also helps to prevent megaloblastic anemia and other neurological consequences as the severity of deficiency increases.[3,4]
Recently, vitamin D deficiency has received significant attention as a contributor to health status. It has been estimated that over 1 billion people globally have low serum vitamin D levels.[5] However, vitamin D deficiency is widely prevalent despite plentiful sunshine even in tropical countries like India.
Vitamin D deficiency is prevalent all over India. It is vital for bone health and an associated risk factor for certain cancers, heart disease, autoimmune diseases, type 2 diabetes, depression, and chronic diseases.[6]
In a meta-analysis conducted by Venkatesh et al.,[7] the prevalence of vitamin B12 and vitamin D3 deficiencies was found to be 53% (95% CI: 0.41, 0.64) and 61% (95% CI: 0.56, 0.65), respectively. Additionally, an intergenerational decline in vitamin D status has been observed among teachers and students.[8]
Both vitamin B12 deficiency as well as vitamin D deficiency problems are major ones with only the tip of the iceberg visible. Also, there is a lack of research on burden in the urban and rural areas.
Against this background, the study estimated the prevalence of deficiencies in vitamin D3 and vitamin B12 within both urban and rural populations in the vicinity of Pune. The secondary objectives encompassed the examination of associations between vitamin B12 deficiency and various socio-demographic factors, dietary habits, addictive behaviors, sources and treatment methods of drinking water, and vitamin supplementation. Additionally, our investigation sought to explore associations between vitamin D deficiency and socio-demographic parameters, dietary patterns, diverse occupations, and engagement in outdoor activities.
Materials and Methods
A community-based cross-sectional analytical study was conducted from March 1, 2021 to December 10, 2022 among participants residing in the area covered by the Urban Health Training Centre (Ajmera, Pimpri, Pune) and Rural Health Training Centre (Alandi, Pune) of a medical college in Pimpri, Pune, Maharashtra.
Participants aged between 18 years and 50 years of age who were residents of the field practice areas and willing to give consent to the study constituted the study population. Participants not willing to consent, acutely ill/bedridden, and those taking or have taken supplements in the past 6 months constituted the exclusion criteria and were excluded.
After obtaining approval number DPU/EC/115/17 from the Institute Ethics Committee (IEC) of the Dr. D.Y. Patil Medical College Hospital and Research Centre, data collection was started. Informed consent was taken prior to obtaining the participant’s details.
Sample size: Community studies on vitamin D3 deficiency in rural and urban areas showed a prevalence of 68% by Goswami et al.[9] and 94% by Rao Vupputuri et al.,[10] respectively. Considering these proportions, at 5% alpha and 80% power, the minimum sample size required for comparison was calculated to be 40 each in rural and urban areas.[11] The software used for the calculation was Statulator (online calculator) and MedCalc software.[11] However, we planned to take a minimum of 50 participants each in rural and urban areas.
Sampling technique: The sampling frame was obtained from the registers of the Urban Health Training Centre (UHTC) and Rural Health Training Centre (RHTC) of the medical college. All the households residing in the area and covered under UHTC and RHTC were enlisted. Following this simple random sampling technique was conducted to select the study participants. If the selected study participant was unwilling or met exclusion criteria or if the door was locked, the adjacent household was considered for the study participation. A few extra samples were collected upon the participant’s request, and hence, the final sample for the urban area was 67 and for rural area, it was 54.
Data collection: Study details were explained to each of the potential participants, and informed consent was obtained. After obtaining the informed consent, demographic variables consisting of age, gender, religion, education, and occupation, source of drinking water, method of purification, were recorded. Details regarding dietary habits, past drug/supplement history, type of outdoor activity, and exercise were asked. Symptoms of deficiency regarding vitamin B12 and vitamin D3, like fatigue, stomach upset, tingling/numbness, depression, pain in bones, muscles, dental problems, and if any other were asked for. Participants were asked for overnight fasting, and the following day under strict aseptic conditions, 5 mL venous blood was collected in plain bulbs and transported to the Central Clinical Laboratory of the medical college maintaining the cold chain.
Test and principle: Serum vitamin B12 and vitamin D levels were estimated using a kit developed by Roche Diagnostics (Roche Diagnostics, Mannheim, Germany). Cut-off levels for vitamin B12 – The biochemical vitamin B12 deficiency was defined at a concentration below < 200 pg/mL, whereas at levels 350 pg/mL, it was taken as borderline deficiency. Cut-off levels for vitamin D deficiency were defined as serum vitamin D3 < 20 ng/mL, insufficiency as 20–29 ng/mL, and sufficiency as ≥ 30 ng/mL.
Data analysis: The data was entered in Microsoft Excel 365 and analyzed using Jamovi v2.4.11.[12] Categorical variables were expressed in terms of frequency and percentages, and continuous variables were expressed as mean and standard deviation or median and interquartile range where applicable. The normality of the continuous variables was assessed using the Shapiro-Wilks test. Univariate analysis (Chi-squared test) was conducted to check the significance of categorical data, and the strength of association represented as odds ratio (OR), student’s t-test, or Mann-Whitney U test was applied to compare the continuous data. In all the tests performed, P < 0.05 was considered to be statistically significant. Six participants (five urban and one rural) were excluded from some analysis due to the unavailability of complete information.
Results
A total of 121 participants were interviewed, and blood samples were collected. Out of these, 67 (55.4%) were from urban areas, and 54 (44.6%) were from rural areas. There were 48 (39.7%) males and 73 (60.3%) females; their distribution across rural and urban areas was not statistically significant. The mean (SD) age of participants was 48.55 (14.16) and 46.56 (15.28) in urban and rural areas, respectively [Table 1]. Most urban participants (67.2%) worked indoors, as opposed to 32.8% in rural areas. A mixed diet was followed by most of the urban participants (67.74%), whereas 54.71% of the rural participants followed a vegetarian diet, and these proportions were significantly different (P = 0.015). Reverse osmosis (RO) water consumption was found to be significantly higher in the rural population (84.90%) as compared to urban areas (54.83%). Over 69.4% of the urban participants had education of graduation or above, while 79.24% of the rural participants studied until senior secondary school.
Table 1.
Characteristics of the study population, rural, and urban comparison
| Characteristics | Categories | Urban, n (%) | Rural, n (%) | Total, n (%) |
|---|---|---|---|---|
| Religion | Hindu | 54 (51.9%) | 50 (48.1%) | 104 (86.0%) |
| Christian | 7 (70.0%) | 3 (30.0%) | 10 (8.3%) | |
| Muslim | 5 (100.0%) | 0 (0.0%) | 5 (4.1%) | |
| Others | 1 (50.0%) | 1 (50.0%) | 2 (1.7%) | |
| Total | 67 (55.4%) | 54 (44.6%) | 121 (100%) | |
| Gender | Male | 28 (58.3%) | 20 (41.7%) | 48 (39.7%) |
| Female | 39 (53.4%) | 34 (46.6%) | 73 (60.3%) | |
| Total | 67 (55.4%) | 54 (44.6%) | 121 (100%) | |
| Education | Uneducated | 1 (7.7%) | 12 (92.3%) | 13 (11.3%) |
| Till upper primary | 8 (36.4%) | 14 (63.6%) | 22 (19.1%) | |
| Till senior secondary | 28 (63.6%) | 16 (36.4%) | 44 (38.2%) | |
| Graduation and above | 25 (69.4%) | 11 (30.6%) | 36 (31.3%) | |
| Total | 62 (53.9%) | 53 (46.1%) | 115 (100%) | |
| Type of occupation | Indoor | 45 (67.2%) | 22 (32.8%) | 67 (58.3%) |
| Outdoor | 17 (35.4%) | 31 (64.6%) | 48 (41.7%) | |
| Total | 62 (53.9%) | 53 (46.1%) | 115 (100%) | |
| Dietary preference | Vegetarian | 20 (40.8%) | 29 (59.2%) | 49 (42.6%) |
| Mixed | 42 (63.6%) | 24 (36.4%) | 66 (57.4%) | |
| Total | 62 (53.9%) | 53 (46.1%) | 115 (100%) | |
| RO water consumption | Yes | 34 (43.0%) | 45 (57.0%) | 79 (69.3%) |
| No | 28 (77.8%) | 8 (22.2%) | 35 (30.7%) | |
| Total | 62 (53.9%) | 53 (46.1%) | 115 (100%) |
Six participants (five urban and one rural) were excluded from some analysis due to the unavailability of complete information
There was no significant difference in age between the two groups, with the urban participants having a mean age of 48.55 years and the rural participants 46.56 years (P = 0.439). Similarly, there was no notable difference in height, as both groups had a mean height of 1.58 meters (P = 0.838). However, significant differences were found in weight and BMI. The urban participants had a higher mean weight (65.31 kg) compared to the rural participants (59.15 kg) (P = 0.010), and their BMI was also significantly higher (26.25 vs. 23.52, P = 0.003), indicating a greater prevalence of overweight or obesity in the urban population.
Prevalence of deficiency for vitamin B12 was seen in 70 (58%) of the total participants with rural participants in higher proportions compared to urban participants, 35 (65%) vis-a-vis 35 (52%). In contrast, vitamin D3 deficiency was in higher proportions of the urban population, 49 (73%) vs. 33 (61%) compared to rural participants. Detailed distribution of serum vitamin categories and various population characteristics are presented in Table 2. Serum vitamin B12 deficiency was higher in males compared to females, and this difference was statistically significant, 34 (71%) vis-a-vis 36 (49%), P = 0.022. However, no gender variations were seen for vitamin D3 deficiency. Participant’s religion did not affect their serum vitamin status. Relative proportions of deficiency were less in participants with education of graduation and above 36% compared to other education groups who had >60% deficiency for vitamin B12, but this was not seen for vitamin D3 status, and the differences were not statistically significant. Participants with vegetarian diet choices were significantly in higher proportions for vitamin B12 deficiency, 37 (76%) vs. 30 (46%), P = 0.001. In contrast, participants consuming a mixed diet were in higher proportions of vitamin D3 deficiency compared to vegetarians, 48 (73%) vs. 30 (61%), and this was not statistically significant. Other variables such as RO water consumption, having taken supplements more than 2 years ago, working indoors or outdoors, were not significantly associated with vitamin D3 and vitamin B12 deficiency.
Table 2.
Distribution of serum vitamin categorization across population characteristics
| Variables and categories | Serum vitamin B12 deficient, n (%) | Insufficient, n (%) | Sufficient, n (%) | Serum vitamin D3 deficient, n (%) | Insufficient, n (%) | Sufficient, n (%) |
|---|---|---|---|---|---|---|
| Place of living | ||||||
| Urban | 35 (52%) | 18 (27%) | 14 (21%) | 49 (73.13%) | 9 (13.43%) | 9 (13.43%) |
| Rural | 35 (65%) | 13 (24%) | 6 (11%) | 33 (61.11%) | 15 (27.78%) | 6 (11.11%) |
| Total | 70 (58%) | 31 (26%) | 20 (17%) | 82 (67.77%) | 24 (19.83%) | 15 (12.4%) |
| Sex | ||||||
| Male | 34 (71%) | 11 (23%) | 3 (6%) | 36 (75%) | 7 (14.58%) | 5 (10.42%) |
| Female | 36 (49%) | 20 (27%) | 17 (23%) | 46 (63.01%) | 17 (23.29%) | 10 (13.7%) |
| Total | 70 (58%) | 31 (26%) | 20 (17%) | 82 (67.77%) | 24 (19.83%) | 15 (12.4%) |
| Education | ||||||
| Uneducated | 9 (69%) | 1 (8%) | 3 (23%) | 9 (69.23%) | 2 (15.38%) | 2 (15.38%) |
| Primary | 14 (64%) | 4 (18%) | 4 (18%) | 12 (54.55%) | 5 (22.73%) | 5 (22.73%) |
| Secondary | 31 (71%) | 6 (14%) | 7 (16%) | 32 (72.73%) | 9 (20.45%) | 3 (6.82%) |
| Graduate | 13 (36%) | 18 (50%) | 5 (14%) | 25 (69.44%) | 7 (19.44%) | 4 (11.11%) |
| Total | 67 (58%) | 29 (25%) | 19 (17%) | 78 (67.83%) | 23 (20%) | 14 (12.17%) |
| Occupation | ||||||
| Indoor | 35 (52%) | 18 (27%) | 14 (21%) | 45 (67.16%) | 12 (17.91%) | 10 (14.93%) |
| Outdoor | 32 (67%) | 11 (23%) | 5 (10%) | 33 (68.75%) | 11 (22.92%) | 4 (8.33%) |
| Total | 67 (58%) | 29 (25%) | 19 (17%) | 78 (67.83%) | 23 (20%) | 14 (12.17%) |
| RO water consumption | ||||||
| Yes | 44 (56%) | 23 (29%) | 12 (15%) | 51 (64.56%) | 18 (22.78%) | 10 (12.66%) |
| No | 23 (64%) | 6 (17%) | 7 (19%) | 27 (75%) | 5 (13.89%) | 4 (11.11%) |
| Total | 67 (58%) | 29 (25%) | 19 (17%) | 78 (67.83%) | 23 (20%) | 14 (12.17%) |
| Dietary preference | ||||||
| Vegetarian | 37 (76%) | 10 (20%) | 2 (4%) | 30 (61.22%) | 13 (26.53%) | 6 (12.24%) |
| Mixed | 30 (46%) | 19 (29%) | 17 (26%) | 48 (72.73%) | 10 (15.15%) | 8 (12.12%) |
| Total | 67 (58%) | 29 (25%) | 19 (17%) | 78 (67.83%) | 23 (20%) | 14 (12.17%) |
Place of living: Vitamin B12, χ2=2.64, P=0.267; Vitamin D3, χ2=3.87, P=0.144. Sex: Vitamin B12, χ2=7.63, P=0.022*; Vitamin D3, χ2=1.972, P=0.373. Education: Vitamin B12, χ2=18.191, P=0.006*; Vitamin D3, χ2=2.317, P=0.509. Occupation: Vitamin B12, χ2=3.031, P=0.22; Vitamin D3, χ2=1.359, P=0.507. RO water consumption: Vitamin B12, χ2=2.075, P=0.354; Vitamin D3, χ2=1.425, P=0.49. Dietary preference: Vitamin B12, χ2=13.141, P=0.001*; Vitamin D3, χ2=2.37, P=0.306
Symptoms of vitamin D3 such as fatigue, bone/muscle pains, dental problems, or other non-specific symptoms were not associated with the serum vitamin deficiency status [Table 3]. For vitamin B12, the deficiency was significantly associated with symptoms of tingling/numbness. Other symptoms of deficiency such as stomach upset, depression, fatigue, and serum deficiency for vitamin B12 were not significantly associated [Table 4].
Table 3.
Association of symptoms of deficiency with serum Vitamin D3 deficiency status
| Serum vitamin deficiency vs. symptoms of deficiency | Present, n (%) | Absent, n (%) | Total | Chi-squared, P |
|---|---|---|---|---|
| Serum Vitamin D3 | Fatigue | |||
| Deficient | 31 (39.74) | 47 (60.26) | 78 (67.83) | Chi-squared (1)=3.926, P=0.048 |
| Not-deficient | 22 (59.46) | 15 (40.54) | 37 (32.17) | Odds ratio=0.45 |
| Total | 53 (46.09) | 62 (53.91) | 115 (100) | |
| Serum Vitamin D3 | Bone/Muscle pains | |||
| Deficient | 47 (60.26) | 31 (39.74) | 78 (67.83) | Chi-squared (1)=0.397, P=0.529 |
| Not-deficient | 20 (54.05) | 17 (45.95) | 37 (32.17) | Odds ratio=1.29 |
| Total | 67 (58.26) | 48 (41.74) | 115 (100) | |
| Serum Vitamin D3 | Dental Problems | |||
| Deficient | 11 (14.1) | 67 (85.9) | 78 (67.83) | Chi-squared (1)=1.029, P=0.31 |
| Not-deficient | 8 (21.62) | 29 (78.38) | 37 (32.17) | Odds ratio=0.59 |
| Total | 19 (16.52) | 96 (83.48) | 115 (100) | |
| Serum Vitamin D3 | Others/non-specific symptoms | |||
| Deficient | 4 (5.13) | 74 (94.87) | 78 (67.83) | Fisher exact P=0.268 |
| Not-deficient | 4 (10.81) | 33 (89.19) | 37 (32.17) | Odds ratio=0.45 |
| Total | 8 (6.96) | 107 (93.04) | 115 (100) |
Table 4.
Association of symptoms of deficiency with serum Vitamin B12 deficiency status
| Serum vitamin deficiency vs. symptoms of deficiency | Present, n (%) | Absent, n (%) | Total | Chi-squared, P |
|---|---|---|---|---|
| Serum vitamin B12 | Fatigue | |||
| Deficient | 30 (44.78) | 37 (55.22) | 67 (58.26) | Chi-squared (1)=0.111, P=0.739 |
| Not-deficient | 23 (47.92) | 25 (52.08) | 48 (41.74) | Odds ratio=0.88 |
| Total | 53 (46.09) | 62 (53.91) | 115 (100) | |
| Serum vitamin B12 | Stomach upset | |||
| Deficient | 9 (13.43) | 58 (86.57) | 67 (58.26) | Chi-squared (1)=0.238, P=0.626 |
| Not-deficient | 5 (10.42) | 43 (89.58) | 48 (41.74) | Odds ratio=1.33 |
| Total | 14 (12.17) | 101 (87.83) | 115 (100) | |
| Serum vitamin B12 | Tingling/Numbness | |||
| Deficient | 17 (25.37) | 50 (74.63) | 67 (58.26) | Chi-squared (1)=5.223, P=0.022 |
| Not-deficient | 22 (45.83) | 26 (54.17) | 48 (41.74) | Odds ratio=0.40 |
| Total | 39 (33.91) | 76 (66.09) | 115 (100) | |
| Serum vitamin B12 | Depression | |||
| Deficient | 5 (7.46) | 62 (92.54) | 67 (58.26) | Fisher exact P=1 |
| Not-deficient | 4 (8.33) | 44 (91.67) | 48 (41.74) | Odds ratio=0.88 |
| Total | 9 (7.83) | 106 (92.17) | 115 (100) | |
| Serum Vitamin B12 | Others/Non-specific symptoms | |||
| Deficient | 4 (5.97) | 63 (94.03) | 67 (58.26) | Fisher exact P=0.718 |
| Not-deficient | 4 (8.33) | 44 (91.67) | 48 (41.74) | Odds ratio=0.69 |
| Total | 8 (6.96) | 107 (93.04) | 115 (100) |
Summary values of serum vitamin D3 in both rural and urban participants were in the deficient category. The median value among urban participants was 13.3 ng/mL and 19.0 ng/mL in rural participants; this difference was statistically significant, P = 0.017. In contrast, serum vitamin B12 values were significantly higher in urban participants. Urban participants had a median value of 195 pg/mL, whereas the rural participants had a median value of 163 pg/mL, P = 0.004. [Table 5] For both vitamin D3 and B12, the median values were in the deficient category with respect to the reference values.
Table 5.
Summary values of serum vitamin D3 and vitamin B12
| Variables | Region | n | Mean (SD) | Median (Q3, Q1) | Mann-Whitney U Test (P) | Effect size |
|---|---|---|---|---|---|---|
| Serum vitamin B12 (pg/mL) | Urban | 67 | 254.8 (182.21) | 195 (277.5, 147) | U=1253, P=0.004 | 0.308 |
| Rural | 54 | 185.5 (108.2) | 163 (221.5, 104.5) | |||
| Serum vitamin D3 (ng/mL) | Urban | 67 | 17.8 (13.8) | 13.3 (20.6, 8.85) | U=1352, P=0.017 | 0.253 |
| Rural | 54 | 19.0 (8.54) | 16.9 (22.1, 13.25) |
Data was not normally distributed, and hence, non-parametric test was performed
Discussion
This study reveals that more than half of the participants from both rural and urban areas were deficient in serum vitamin D3 and vitamin B12.
Vitamin D3
For vitamin D3, urban participants had higher deficiency 73% compared to rural participants 61%. These findings align with several community-based studies that have reported widespread vitamin D3 deficiency (VDD). Rao Vupputuri et al.[10] reported 94% deficiency among urban adults of Delhi, while Marwaha et al.[13] found a 91% deficiency rate in a similar population. Goswami et al.[9] observed a 68.5% deficiency among the rural adults of Delhi, and Misra et al.[14] reported an even higher rate of 90.8% among rural women in Ballabgarh. Among the adults aged more than 50 years in Varanasi, Agrawal and Sharma[15] reported 58% deficiency. Menon AS et al.[16] in their study among military recruits reported a deficiency of 48% and an insufficiency of 32%. These comparisons highlight that vitamin D3 deficiency is a pervasive issue across both rural and urban settings, with a majority of studies reporting deficiency rates above 50%.
The mean serum vitamin D3 levels observed in this study (19.0 ng/mL for rural and 17.8 ng/mL for urban participants) are consistent with findings from other studies. The mean levels of serum vitamin D3 among the adults of Hyderabad as reported by Suryanarayana et al.[17] were 19.3 ng/mL. Goswami et al.[9] presented a mean value of 36.4 nmol/L which corresponds to 14.56 ng/mL. Menon et al.[16] reported a mean value of 21.44 ng/mL slightly higher than our results but potentially due to the healthier lifestyle and status of the recruits. Rao Vupputuri et al.[10] from their cohort of 105 participants reported an average serum vitamin D3 value of 9.8 ng/mL in their study subjects which is of deficient category similar to our study results. These findings consistently point to a trend of deficient vitamin D3 levels across different populations.
Despite exploring various factors, our study found no significant correlation between BMI and serum vitamin D3 levels (Pearson’s r = −0.068, P = 0.473), which aligns with the results from Menon et al.[16] (Pearson’s r = 0.044, P = 0.523) and Misra et al.[14] among their rural women participants. Diet did not influence deficiency status and no difference between vegetarians and participants taking mixed diets.
Gender differences were also minimal, with men showing only slightly higher vitamin D3 levels than women. These results were similar in other studies as well. Education did not influence vitamin D3 status as comparable proportions were deficient across various education categories. Misra et al.[14] also found no association of education and occupation with deficiency. Similarly in our study, working outdoors or indoors was not significantly associated with deficiency.
Vitamin B12
In this study, 70 participants (58%) were found to be deficient in vitamin B12, with rural participants showing a higher deficiency rate (65%) compared to urban participants (52%). This higher prevalence in rural areas may be partly attributed to the higher proportion of vegetarians in these communities. Similar results were reported by Yajnik et al.,[18] from Pune, where 67% of participants were vitamin B12 deficient, all of whom were vegetarians. Other studies from India, such as those by Singla et al.,[19] Gupta et al.,[20] and Raizada et al.,[21] have reported deficiency rates ranging from 42% to 66%. Certain studies also have reported a higher prevalence, Sonthalia et al.,[22] 90%. Bharti et al.[23] studied on patients with depressive disorder, and others studied on diabetic patients and corporate employees.[19,21,22,23,24,25] The variation in prevalence across studies could be due to differences in participant selection, with some studies focusing on specific populations, such as patients with depressive disorders or premature canities.
Interestingly, gender differences in vitamin B12 deficiency were noted, with men showing higher deficiency rates than women in both rural (80% males vs. 55% females) and urban (64% males vs. 44% females) areas. This finding is consistent with the conclusions of Jayashri Ramamoorthy et al.,[26] who identified men and vegetarians as being at higher risk for vitamin B12 deficiency. Margalit et al.[27] also found that men are more susceptible to deficiency, possibly due to genetic factors rather than dietary habits.
While some studies have hypothesized that the use of RO water could contribute to vitamin B12 deficiency, no significant differences were observed in this study.[20] Symptoms of deficiency were not significantly associated with serum vitamin deficiency status. Only VDD was significantly associated with fatigue as a symptom. This discrepancy raises questions about the current normative values for vitamin B12 and vitamin D3 in the Indian population and suggests the need for further research.
Limitations
One key limitation of this study is the lack of consensus on vitamin D3 cut-off values for the Indian population. The current cut-offs are from the western population and developed by delineating the ricket children from healthy ones. This limitation may affect the accuracy of deficiency prevalence estimates in this study. Future research could benefit from more detailed data on participants’ physical activity and sun exposure, which are important factors influencing vitamin D3 levels.
Conclusions
Vitamin B12 and vitamin D3 deficiency are quite common and often underdiagnosed until severe deficiency. The study presents a high prevalence of both vitamin B12 and vitamin D3 deficiency in rural and urban participants. Urban participants were more deficient for vitamin D3, whereas rural participants were more deficient for vitamin B12. Appropriate health promotive activities to be conducted in both rural and urban areas like engaging actively outdoors and encouraging a nutritious balanced diet. Ongoing fortification of milk and oils can be encouraged. The lack of correlation between symptoms and deficiency underscores the need for careful prescription of supplements and raises important questions about the appropriate diagnostic criteria for these conditions in the Indian population.
Conflicts of interest
There are no conflicts of interest.
Acknowledgement
This study was funded by Dr. D. Y. Patil Medical College Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth (Deemed to be University) Pimpri, Pune, India. Beyond the institution, the authors would like to thank all the phlebotomists and medical social workers of rural and urban health training centres for their cooperation in the field and centre. Full data deidentified for participant name would be made available at the reasonable request made to the corresponding author.
Funding Statement
This study was funded by Dr. D. Y. Patil Medical College Hospital and Research Centre, Dr. D. Y. Patil Vidyapeeth (Deemed to be University) Pimpri, Pune, India. The funders had no role in the study.
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