Prevalence and Risk Factors for Vitamin C Deficiency in
North and South India: A Two Centre Population Based
Study in People Aged 60 Years and Over
Ravilla D. Ravindran1, Praveen Vashist2, Sanjeev K. Gupta2, Ian S. Young3, Giovanni Maraini4, Monica
Camparini4, R. Jayanthi1, Neena John2, Kathryn E. Fitzpatrick5, Usha Chakravarthy6, Thulasiraj D.
Ravilla7, Astrid E. Fletcher5*
1Aravind Eye Hospital Pondicherry, Pondicherry, India, 2Dr. Rajendra Prasad Center for Ophthalmic Sciences, All India Institute of Medical Sciences, New Delhi, India,
3Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Queen’s University Belfast, Belfast, United Kingdom, 4Dipartimento di Scienze Otorino-
Odonto-Oftalmologiche e Cervico Facciali, Sezione di Oftalmologia, Universita ` degli Studi di Parma, Parma, Italy, 5Faculty of Epidemiology and Population Health, London
School of Hygiene and Tropical Medicine, London, United Kingdom, 6Centre for Vision and Vascular Science, School of Medicine, Dentistry and Biomedical Sciences,
Queen’s University Belfast, Belfast, United Kingdom, 7Lions Aravind Institute of Community Ophthalmology, Madurai, India
Background: Studies from the UK and North America have reported vitamin C deficiency in around 1 in 5 men and 1 in 9
women in low income groups. There are few data on vitamin C deficiency in resource poor countries.
Objectives: To investigate the prevalence of vitamin C deficiency in India.
Design: We carried out a population-based cross-sectional survey in two areas of north and south India. Randomly sampled
clusters were enumerated to identify people aged 60 and over. Participants (75% response rate) were interviewed for
tobacco, alcohol, cooking fuel use, 24 hour diet recall and underwent anthropometry and blood collection. Vitamin C was
measured using an enzyme-based assay in plasma stabilized with metaphosphoric acid. We categorised vitamin C status as
deficient (,11 mmol/L), sub-optimal (11–28 mmol/L) and adequate (.28 mmol/L). We investigated factors associated with
vitamin C deficiency using multivariable Poisson regression.
Results: The age, sex and season standardized prevalence of vitamin C deficiency was 73.9% (95% confidence Interval, CI
70.4,77.5) in 2668 people in north India and 45.7% (95% CI 42.5,48.9) in 2970 from south India. Only 10.8% in the north and
25.9% in the south met the criteria for adequate levels. Vitamin C deficiency varied by season, and was more prevalent in
men, with increasing age, users of tobacco and biomass fuels, in those with anthropometric indicators of poor nutrition and
with lower intakes of dietary vitamin C.
Conclusions: In poor communities, such as in our study, consideration needs to be given to measures to improve the
consumption of vitamin C rich foods and to discourage the use of tobacco.
Citation: Ravindran RD, Vashist P, Gupta SK, Young IS, Maraini G, et al. (2011) Prevalence and Risk Factors for Vitamin C Deficiency in North and South India: A
Two Centre Population Based Study in People Aged 60 Years and Over. PLoS ONE 6(12): e28588. doi:10.1371/journal.pone.0028588
Editor: Abdisalan Mohamed Noor, Kenya Medical Research Institute - Wellcome Trust Research Programme, Kenya
Received June 3, 2011; Accepted November 11, 2011; Published December 6, 2011
Copyright: ? 2011 Ravindran et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits
unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The study was funded by the Wellcome Trust UK, Grant 073300 (www.wellcome.ac.uk). The funder had no role in study design, data collection and
analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: email@example.com
Vitamin C (ascorbic acid) plays a major role in human
metabolism ranging from the synthesis of collagen, carnitine and
norepinephrine to a large number of antioxidant activities .
Humans are unable to synthesize vitamin C and are dependent on
dietary sources, mainly fruit and vegetables. Even in high income
countries population-based studies have reported blood levels of
vitamin C in the range indicating deficiency in around 1 in 5 men
and 1 in 9 women in low income groups [2,3,4,5,6]. Smokers, non-
users of vitamin supplements and those consuming less than the
recommended dietary intakes of vitamin C were subgroups shown
to be at higher risk in these studies. In the US where supplement
use is common among older people, vitamin C deficiency is lower
than in younger age groups [3,5], but in the UK with a lower use
of supplements, higher vitamin C deficiency and lower dietary
intakes  have been reported in older people. There are scarce
data on vitamin C deficiency in resource-poor countries where
vitamin C deficiency might be expected to be more prevalent. A
systematic review found that a third of reproductive age women in
resource-poor settings had dietary vitamin C intakes below the
Estimated Average Requirements (EAR) rising to nearly 50% in
Africa and South East Asia . The limited data on older people
in India show high rates of malnutrition . Tobacco use is
common in India with a third of adults smoking or chewing
tobacco  . These factors: poor diets, especially in the older age
PLoS ONE | www.plosone.org1December 2011 | Volume 6 | Issue 12 | e28588
group, and high use of tobacco suggest that vitamin C deficiency
might be high in the older Indian population but currently no
studies have investigated this or whether risk factors for vitamin C
deficiency differ from those reported in high income populations.
We aimed to estimate the prevalence of vitamin C deficiency in an
older population in India and examine the factors associated with
Participants gave full informed written consent. Illiterate
subjects had the information leaflet read out to them and provided
a thumb impression. The study complied with the guidelines in the
Declaration of Helsinki and ethics approval was received from the
Indian Council for Medical Research, Research Ethics Commit-
tees of the All India Institute of Medical Sciences, Aravind Eye
Hospital, London School of Hygiene and Tropical Medicine and
Queen’s University Belfast.
The India age-related eye disease study (INDEYE) is a
population-based study in two geographically different locations in
India. The study sampling has been described in detail elsewhere
. We aimed to enroll 3000 people aged $60 years in each of the
two study locations allowing for a response rate of 80%. The sample
size calculations were based on the estimated prevalence of age-
related macular degeneration. People aged 60 and over were
identified from household enumeration of randomly sampled
clusters in Gurgaon district, Haryana state, north India, and
Pondicherry and Cuddalore district in Tamil Nadu, south India.
These areas were chosen to represent a mix of rural and urban
populations served by the participating eye hospitals (Dr Rajendra
Prasad Center of Ophthalmic Sciences, (RPC), All India Institute of
Medical Sciences, Delhi and the Aravind Eye Hospital (AEH),
Pondicherry). Gurgaon city and Pondicherry city were excluded due
people aged 60 and over were invited to take part in the study.
Data collection took place between September 2004 and
December 2006. Enumerators collected household and individual
socio-demographic and economic data. Fieldworkers interviewed
participants at home with a structured questionnaire which
included current and past tobacco use (smoking beedie (small
hand rolled cigarettes) and/or cigarettes, chewing or inhaling),
current and past alcohol use and type of cooking fuels. Diet was
assessed by 24 hour recall. Within a week of the home interview
participants were brought to the base hospital for the clinical
examination which included anthropometry, an eye examination
and blood sample collection. All examinations took place in the
morning. Anthropometry included measurement of height,
weight, and mid-upper arm circumference (MUAC). Participants
were asked to remove heavy outer garments and take off their
shoes. Standing height was measured to the nearest 0.1 cm using a
portable stadiometer. Weight was measured using electronic scales
and recorded to the nearest 0.1 kilogram. MUAC was measured at
the mid-point between the inferior border of the acromion process
(shoulder bone) and the tip of the olecranon process (elbow) to the
nearest 0.1 cm on the bare left arm, using a fibre glass insertion
tape. People were asked to bring medications or nutritional
supplements to the hospital and details were recorded.
For each participant a sample of 15 ml blood was collected in a
shaded room in two different vacutainer tubes (10 ml clotted and
5 ml EDTA unclotted). The EDTA unclotted sample was kept in
the refrigerator and processed within 2 hours after collection. The
EDTA samples were centrifuged at 3000 rpm at 4uC (using a cold
centrifuge) for 15 minutes. After centrifugation, exactly 100 ml of
plasma were transferred to each of two storage tubes using a
Merck graduated pipette and exactly 900 ml of 5% metapho-
sphoric acid (MPA) were added to each tube and the contents were
mixed by gentle inversion without shaking. The aliquoted samples
were kept in the fridge until the samples of the last participant of
the morning had been processed and all samples were placed in
the dedicated study freezer (270uC) for storage until shipment.
Fresh MPA solution was made up every two weeks by dissolving
5 g of metaphosphoric acid crystals in 100 ml of distilled water.
The solution was placed in a dark glass bottle and kept in the
refrigerator at 4uC. The median time of storage of blood samples
was 1.1 years. Samples were subsequently shipped by air to
Queen’s University Belfast in dry ice using a courier service with
tracking and monitoring of sample temperature throughout the
shipping process. Vitamin C was measured by automated
fluorimetric assay  on a Cobas FARA centrifugal analyzer
(Roche Diagnostics, Switzerland). The limit of detection of the
assay was 2 mmol/L.
Assays were standardised against the US National Institute of
Standards and Technology (NIST) standard reference materials.
We also collected from each participants a non-fasting sample of
capillary blood which was assessed for glucose (CBG) using a
reagent strip test and reflectance meter.
Data preparation and Statistical Analysis
Nutrient intakes of energy and vitamin C were calculated from
the individual food items in the 24 hour recall using the Indian
food composition tables . Dietary vitamin C was adjusted for
total energy intake using the residual model of Willett . Plasma
vitamin C status was categorised as deficient (,11 mmol/L), sub-
optimal (11–28 mmol/L) and adequate (.28 mmol/L). This
categorisation was used by previous authors [2,4] and based on
expert committee recommendation . Principal component
analysis was used to derive a socio-economic status index (SES)
(based on caste, landholding, type of roof and number of rooms in
house). Current use of household cooking fuels was classified as
clean (kerosene, electricity, LPG, Bio gas/gobar gas) or biomass
(wood, crop residues, dung cakes). Alcohol and tobacco use were
categorized as current, or never and past. Body Mass Index (BMI)
was calculated as weight (kg)/ height (cm)2. Nutritional status was
indicated by BMI and MUAC. We used WHO guidelines for
categories of BMI in Asians with underweight defined as ,18.5,
normal weight as $18.5 to ,25, and overweight and obese
defined as $25 .
We defined MUAC values as normal (.23 in men and .22 in
women) or mild malnutrition (22.1-23 in men and 20.1–22 in
women) and moderate to severe malnutrition (,22 in men and
,20 in women) . Diabetes was defined as CBG $110 mg/
dl. We categorised season according to the India Meteoro-
logical Department classification, http://www.imd.gov.in/doc/
climate_profile.pdf (accessed May 3rd2011) using the date of the
clinical examination when the blood sample was collected.
Statistical analysis was carried out using Stata 11 (StataCorp.
2009. Stata Statistical Software: Release 11. College Station, TX:
StataCorp LP.). We estimated the age, sex and season standard-
ized prevalence of vitamin C status in the two study locations using
the total study population as the standard. We undertook
univariable and multivariable Poisson regression to investigate
the association of factors expected a priori to be associated with
plasma vitamin C status: age, sex, socio-economic status, biomass
Vitamin C Deficiency in Older People in India
PLoS ONE | www.plosone.org2December 2011 | Volume 6 | Issue 12 | e28588
cooking fuels, tobacco and alcohol use, diabetes, anthropometry
(BMI, MUAC), season and dietary vitamin C. In these models
dietary vitamin C across the distribution of both locations was
categorised by quartiles. We checked for interactions (p ,0.05) by
location for all variables in the model. Due to correlation between
BMI and MUAC we included these variables separately in
multivariable analysis. In all analyses we took account of the study
design of cluster sampling using either the survey suite of
commands (svy) in Stata to compute standard errors using
linearized variance estimators or by the robust cluster option in
Of 7518 enumerated people aged 60 years and over, 5900
(78%) attended the hospital-based clinical examination of whom
5702 (76%) gave a blood sample. Plasma vitamin C was available
in 5638 (2668 from RPC and 2970 from AEH). Those without
vitamin C data (non responders to the clinical exam and those with
no blood sample) were older, 69.7 years (SD=8) compared to
those with vitamin C data, 67.6 years (SD=6), p ,0.00001. There
were no differences by sex, socio-economic status (or its individual
components of education, caste, or landholding) or by the season
of enumeration of the villages. Dietary measures of vitamin C were
available in 5502 of those with plasma vitamin C. Very few people
(n=69, 1.2%) reported taking any nutritional supplements and all
of these were from south India. Thirty percent of the study
population (n=1692) had plasma levels below 2 mmol/L. The
majority of people with levels below 2 (n=1184) were from north
The age, sex and season standardized prevalence of vitamin C
deficiency was 73.9% (95% Confidence Interval, CI 70.4, 77.5) in
north India and 45.7% (95% CI 42.5, 48.9) in south India
(Table 1). Only 10% of those in the north and a quarter of those in
the south met the criteria for adequate levels. In both locations the
prevalence of vitamin C deficiency was higher in men compared to
women, and increased with increasing age (Table 2). There were
significant associations across the three categories of vitamin C
status (adequate, sub-optimal, deficient) with increasing age, lower
proportions of women, higher proportions of the lowest socio-
economic group, users of biomass cooking fuels, and current
tobacco users (Table 3). The proportions of those with indices of
poor nutrition (BMI of ,18.5 or MUAC ,22 in men and ,20 in
women) increased from adequate status to deficiency. Alcohol use
was rarely reported by women (12 current and 6 past, 1.1% in the
south and one past user in the north). There was no association
between current alcohol consumption and vitamin C status in
men. Being overweight (BMI . 25) was associated with better
vitamin C status (Table 3). There was no association with diabetes.
Dietary vitamin C intakes decreased with poorer plasma vitamin C
status. This difference was most marked in the north, from
31.9 mg/day for those with adequate plasma vitamin C status to
19.5 for those categorized as deficient.
In Poisson regression comparing those with vitamin C
deficiency with those with adequate levels, there were significant
interactions with location and current tobacco use (p=0.001) and
location and season, p ,0.0001) in univariable and multivariable
analyses (Table 4). The association with tobacco use was stronger
in the south (multivariable adjusted prevalence rate ratio, PRR
1.29, 95% CI 1.18, 1.41) compared to the north (PRR of 1.07,
95% CI 1.01, 1.13). The pattern of associations with season varied
according to location. In north India, compared to the winter
season (December to February) the months of June to September,
and October to November were associated with a higher
prevalence of deficiency (multivariable adjusted PRR of 1.27,
95% CI 1.16, 1.38 and 1.27, 95% CI 1.17, 1.38) respectively. In
the south of India the months of March to May and June to
September were associated with a lower prevalence of vitamin C
deficiency, PRRs of 0.83 (95% CI 0.74, 0.94) and 0.73 (95% CI
0.61, 0.89) compared to the winter months. For other variables in
the multivariable analysis significant associations with vitamin C
deficiency remained for age, sex, use of biomass fuels, low BMI
and dietary vitamin C with attenuation of the PRRS compared to
the univariable analysis. Results were similar when MUAC was
included in place of BMI (data not shown).
In multivariable Poisson regression of factors associated with
sub-optimal compared to adequate vitamin C status, only tobacco
Table 1. Age, sex and season-standardized prevalence of
plasma vitamin C adequacy status in people aged 60 years
and over by location in India.
. .28 m mmol/L11–28 m mmol/L
, ,11 m mmol/L
N=2668 n=286n=403 n=1979
95%CI 8.0, 13.5 13.8, 16.870.4, 77.5
N=2970n=774 n=853 n=1343
95%CI22.9, 28.9 26.3, 30.642.5, 48.9
Table 2. Age and sex specific prevalence of plasma vitamin C
deficiency (,11 mmol/L) in people aged 60 years and over by
location in India.
North India South India
95% CI95% CI
Men 1283 77.71407 51.4
70.9, 84.5 47.4, 55.4
61.9, 79.833.9, 45.4
60–64985 68.7 108036.6
60.1, 77.429.5, 43.7
62.9, 81.632.2, 6.3
73.7, 88.033.3, 50.9
70.8, 87.234.2, 55.0
78.3, 91.738.2, 63.2
Vitamin C Deficiency in Older People in India
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use and, in the north, season were associated. The PRRs were
similar to those reported for vitamin C deficiency (tables available
from authors on request). There was no significant interaction
between location and tobacco use. The smaller number in these
analyses limited the power to investigate associations and
We found a high prevalence of vitamin C deficiency in older
people in India; 74% of those in the north of India and 46% in
the south of India were deficient and a further 15% and 28%
respectively had sub-optimal levels. In common with other studies
[3,4,5,6] we found that vitamin C deficiency was more common
in men and in users of tobacco. The lower levels of vitamin C in
smokers partly reflect lower intakes but also a higher rate of
ascorbate turnover possibly due to higher levels of oxidative stress
in smokers . The association with tobacco was observed in
both south and north India but the PRR was higher in the south.
There were differences in the pattern of tobacco use by location.
Tobacco chewing was more common in the south (28%)
compared to the north (2%). Smoking manufactured cigarettes
was rare in both locations (3%) but smoking beedies was higher in
the north (39% compared to 9% in the south). Chewing tobacco
may have a more adverse effect on ascorbate levels compared to
tobacco smoking because the tobacco quid is held in the mouth
for a longer period of time but experimental data are not
Use of biomass fuels was associated with vitamin C deficiency.
The smoke from combustion of biomass fuels includes small
respirable particles, carbon monoxide, nitrogen formaldehyde and
polyaromatic hydrocarbons. Since many of the constituents of
biomass fuels are also found in tobacco smoke  it is likely that
other adverse effects of biomass fuels on vitamin C are similar to
those found for tobacco.
Seasonal differences in vitamin C deficiency varied between the
north and south reflecting the different climatic and agricultural
patterns across the sub-continent. In the north, the highest PRRs
were observed for the main monsoon period (June to September)
compared to the winter. Poor nutritional status in the monsoon
months and higher dietary intakes of vegetables in the winter
period have been reported from studies in the north of the sub-
continent [21,22]. In contrast the monsoon is lighter and later in
the south of India. Dietary vitamin C levels also varied by season
especially in the north (median of 30.6 mg/day in the winter
compared to 15.7 in June to September). In the south the median
values for these periods were 32.1 and 34.8 respectively.
Dietary vitamin C intakes from other studies in India [8,23] are
considerably lower than observed in western populations.
However comparison of intakes of dietary vitamin C across
studies and populations is limited by differences in the dietary
assessment method and the availability of vitamin C data in Food
Composition Tables for foods consumed in specific populations
including values by cooking methods. We used a single 24 hour
recall and the ICMR food composition tables which provide
values of vitamin C from food items common to the Indian
population. A limitation of these tables is that the values are based
on raw foods. Loss of vitamin C occurs with heating and therefore
dietary vitamin C in our study and in other studies in India is
probably overestimated by at least 25% since the most common
method of food preparation in the Indian population is cooking by
heat [24,25]. Although dietary vitamin C intakes are a major
determinant of plasma vitamin C levels, this is difficult to
demonstrate other than in tightly controlled experimental
Table 3. Characteristics by plasma vitamin C status by location in India.
North India South India
Plasma vitamin C
. .28 m mmol/L 11–28 m mmol/L
, ,11 m mmol/L
. .28 m mmol/L 11–28 m mmol/L
, ,11 m mmol/L
N=286N=403N=1979 N=774N=853 N=1343
65.8 (5.9)66.8 (6.1) 68.3 (6.8)
,0.0001 66.9 (6.2)67.1 (6.1) 67.9 (6.6)0.002
182 (63.6)221 (54.8)982 (49.6) 0.03 449 (58.0)494 (57.9) 620 (46.2) 0.0001
41 (14.3)77 (19.1) 463 (23.4) 0.02 139 (18.0)181 (21.2) 346 (25.8)0.02
194 (67.8) 290 (72.0)1641 (82.9) 0.001 349 (45.3)448 (53.0)706 (53.4) 0.1
22 (7.7)46 (11.4) 343 (17.3)0.0172 (9.3) 104 (12.2) 254 (18.9)
Body mass Index
50 (17.5)99 (24.6)698 (35.5)
,0.0001191 (24.7)247 (29.1)476 (35.8)0.002
55 (19.2) 74 (18.4)233 (11.8)0.003 178 (23.0)171 (20.2)206 (15.5) 0.003
151 (52.8)249 (61.8)1141 (57.7)0.1 447 (57.8)459 (53.8) 755 (56.2)0.3
126 (44.1)230 (57.1)1284 (64.9)
,0.0001 248 (32.0)363 (42.6)709 (52.8)
36 (34.6)71 (39.0)447 (44.8)0.1113 (34.8)122 (34.0)271 (37.5)0.6
Dietary vitamin C6
18.0, 50.9 17.5, 44.611.8, 33.524.7, 53.725.1, 49.4 22.9, 48.7
1Mean (Standard Deviation).
2n with characteristic (%).
4Moderate & severe malnutrition defined as a mid-upper arm circumference of ,22 in men and ,20 in women.
51283 men in north India and 1407 men in south India.
6Median, (InterQuartile range) mg/day.
Vitamin C Deficiency in Older People in India
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conditions . In population surveys, dietary assessment methods
including 24 hour recall show only moderate correlations with
plasma vitamin C. A meta-analysis of studies in high income
countries reported correlations between dietary vitamin C from
diet recall (ranging from one day to 12 days) and plasma vitamin C
of 0.46 . The correlation was similar for one day to longer
recall, in studies excluding supplement users, and was higher in
women (r=0.44) than men (r=0.36). In our study the correlation
coefficient between diet and plasma vitamin C was much lower
(r=0.20) and did not vary by sex. The authors of the meta-analysis
concluded the moderate correlations observed might be influenced
by factors including bioavailability, food processing and storage
and recall errors by participants. These limitations are also
applicable to our study.
Table 4. Prevalence Rate Ratios for plasma vitamin C deficiency (,11 mmol/L) compared to adequate (.28 mmol/L).
Univariable analysis Multivariable analysis
95% CIp PRR2
65–69 1.05 0.99, 1.10 1.071.02, 1.12
70–741.11 1.05, 1.171.08 1.03, 1.14
75–79 1.111.04, 1.19 1.091.02, 1.16
1.17 1.09, 1.251.14 1.07, 1.22
Women 0.91 0.86, 0.96
,0.0001 0.930.89, 0.98 0.003
,0.0001 1.03 0.99, 1.070.2
Biomass fuels 1.25 1.14, 1.20
,0.0001 1.03 0.98, 1.09 0.02
Body mass Index
,18.5 1.111.06,1 .16
,0.0001 1.05 1.03, 1.09
$25 0.910.84, 0.96 0.002 0.970.93, 1.02 0.3
Diabetes1.020.97,1.07 0.61.010.97, 1.05 0.6
North India 1.091.02, 1.150.01 1.07 1.01, 1.13 0.02
South India 1.341.19, 1.50
Dietary vitamin C5
.18–29 0.880.83, 0.93 0.990.95, 1.03
.29–44 0.800.76, 0.86 0.950.91, 0.99
.440.73 0.68, 0.77 0.900.86, 0.94
December to February11
March to May 1.110.96, 1.29 0.21.090.95, 1.25 0.2
June to September1.33 1.21, 1.46
,0.0001 1.27 1.16, 1.38
October to November1.27 1.16, 1.40
,0.00011.27 1.17, 1.38
December to February1
March to May 0.86 0.61, 0.910.03 0.83 0.74,0.94 0.003
June to September 0.740.61, 0.91 0.0040.730.61,0.890.001
October to November0.87 0.77, 0.990.040.910.78,1.06 0.2
1Prevalence rate ratios adjusted for age and sex.
2Prevalence rate ratios adjusted for variables in the Table.
4interaction for tobacco use and vitamin C deficiency by location, p=0.001.
5Quartiles of dietary vitamin C (mg/day).
6interaction for season and vitamin C deficiency by location, p ,0.0001.
Vitamin C Deficiency in Older People in India
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Since Vitamin C is degraded by factors such as light,
temperature (above 4uC) and oxidation, considerable care is
required in the collection and processing of samples . We
collected blood in subdued lighting in vacutainer tubes containing
the chelating agent EDTA to prevent the continued oxidation of
vitamin C from metal ions and stored the tubes in a 4uC fridge for
up to 2 hours before cold centrifugation and stabilization with
MPA. Greater degradation of vitamin C with EDTA compared to
heparin treated samples has been reported [29,30]. In a study of 5
people with paired samples analyzed immediately after collection
using the FRASC method, the mean ascorbate was around
50 mmol/L in the EDTA samples compared to around 80 mmol/L
in the heparin samples . Karslen et al found no significant
difference between heparin and EDTA as anticoagulant when
baseline ascorbate levels measured by HPLC were compared, with
a mean 2.8% lower level of vitamin C in EDTA samples .
Delayed ascorbate measurement with samples left at room
temperature showed greater degradation especially for EDTA
samples (e.g. 10% loss at 2 hours compared to 5% heparin).
Heparin samples stored at 4uC for 2 hours showed ,1%
degradation in MPA acidified plasma, compared to 5.6%
degradation in non-acidified plasma and 10% loss for storage for
24 hours. The equivalent data for EDTA was not collected. In
contrast, Ching et al in a study of 10 people reported that samples
treated by heparin, centrifuged and acidified and measured by
HPLC had 7% less ascorbate than EDTA samples treated the
same way ; ascorbate loss was also significantly greater in
heparin samples following a 2 hour delay in separation followed
immediately by centrifugation and acidification (median 18% loss
for heparin compared to 7% for EDTA). Although results from
these small studies are not consistent with respect to heparin
compared to EDTA and show considerable intra individual
variation, all studies confirm the importance of refrigeration at
4uC for as short a period as possible, followed by immediate cold
centrifugation and acidification. Once samples are frozen, plasma
ascorbate is stable over long term storage at 270uC . In our
study the median storage time was just over one year. Although we
had a clear protocol for the collection and processing of samples
and laboratory staff were trained to follow the protocol, we cannot
exclude that errors may have occurred leading to loss of vitamin C
from the samples. Vitamin C showed typical patterns observed
consistently in other studies, such as lower levels in men, in
tobacco users, those with indices of poor nutrition, lower socio-
economic status and an inverse association with age . It is
unlikely that these patterns would be preserved if the blood
samples had degraded randomly but a systematic loss would lead
to an over estimation of the prevalence of vitamin C deficiency.
Quantifying the possible ascorbate loss in our study is uncertain
but based on the literature reviewed above [29,30,31,32] we might
expect only minor degrees of ascorbate loss (possibly up to 10%)
due to pre-analytical factors such as use of EDTA, and delays in
centrifugation and freezing of samples in view of the sample
handling protocol described in this study. However we acknowl-
edge that the losses might be greater since we did not have any
formal methods of quality assurance to ensure the protocol was
followed. The levels for participants in north India in the present
study were very similar to those in a small feasibility study we
conducted previously in Haryana .
We had only a single measurement of plasma and dietary
vitamin C and were unable to ascertain the effects of within person
seasonal changes. Our response rates were acceptable (75%) and
apart from age there was no response bias in sex or socio-
economic status. Since vitamin C deficiency increased with age the
prevalence of vitamin C deficiency might be underestimated.
Our population was primarily rural or from small towns,
characterized by low BMI, high tobacco and biomass fuel use and
low intakes of dietary vitamin C. In 15% the mid-upper arm
circumference values were indicative of moderate to severe
malnutrition. Our results may not apply to middle aged and
younger people, city dwellers or high income groups and studies
are required in these groups.
In addition to low dietary intakes of vitamin C, low plasma
levels of vitamin C in India may also reflect haptoglobin (Hp) allele
status (Hp1 or Hp2). The Hp2 -2 phenotype is substantially higher
in India (around 70–80%) compared to populations of European
ancestry (30–40%), and conversely Hp1-1 is much lower, less than
3% in India compared to around 15–20 % in Europeans .
Studies in Europeans have reported around 20% lower plasma
vitamin C levels in those with the Hp2-2 polymorphism compared
to those with Hp 1-1 . A study of University of Toronto non-
smoking students found vitamin C deficiency in 17% of those with
Hp2-2 compared to 11% of those with either Hp 1-1or 2-1. The
risk of deficiency in those with low dietary intakes of vitamin C
(below recommended intakes) was modified by Hp status; from an
OR of 1.7 for Hp1-1 or 2-1 to an OR of 4..8 for HP2-2 .
These data suggest that the effect of Hp2-2 may be greatest when
dietary intakes of vitamin C are low. No data are presently
available in India on vitamin C and haptoglobin polymorphism.
An important function of haptoglobin is to bind haemoglobin
preventing peroxidation by free iron; the observation of lower
vitamin C levels in Hp2-2 individuals with lower haptoglobin may
reflect the increased depletion of vitamin C due to reduction of
free iron . Haptoglobin polymorphisms might also explain in
part the lower levels of vitamin C reported for South Asians in the
UK compared to those of European or African ancestry  or for
Indians in Singapore compared to Chinese . However the
differences in plasma vitamin C between ethnic groups in these
studies were not large and the mean levels were much higher than
in our study population. The studies on vitamin C in Indian ethnic
groups in Singapore and the UK are in the settings of high income
countries. Indians in these settings are characterized by BMIs in
the normal to overweight range, more central obesity and higher
dietary energy intakes. Although data are sparse it is likely that
dietary intakes of vitamin C in Indians are also higher in high
income settings, probably reflecting better nutrition of the Indian
ethnic groups in contrast to our study participants. In a study in
the UK, children of Indian ethnicity had slightly lower dietary
intakes compared to white European children but both groups had
intakes well above the recommended intakes for their age group
. Currently there are limited data on other genetic modifiers of
vitamin C levels [41,42] and no studies have been carried out in
The majority of previous reports on vitamin C deficiency from
population based studies have taken place in the UK or North
America. In these studies the prevalence of vitamin C deficiency
ranged from 26% of men and 14% of women aged 25 to 74 years
in the Glasgow MONICA study ,25% of men and 16% of
women aged 19 years and over in the UK Low Income Diet and
Nutrition Survey, 14% of nonsmoking women and men aged
20–29 years in the University of Toronto campus . In two
waves of the US Nutrition and Health Examination Study of
people aged 20 years and over, vitamin C deficiency was reported
in 18% of men and 12% of women for 1998–1994 , reducing to
10% and 7% in the 2003–2004 survey; the prevalence for those in
the lower income groups was double that of the high income
groups at both time periods . Only two studies have been
conducted outside high income countries including one from
India. A nationally representative population study from Mexico
Vitamin C Deficiency in Older People in India
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reported a 40% prevalence of deficiency in women of childbearing
age . Men and older people were not included in the study. In
a small study of 322 people aged 20–50 years from western India,
vitamin C deficiency was found in 9.6% of men and 13.0 % of
women, and just over a half had levels in the sub-optimal range
In conclusion, we found vitamin C deficiency in a substantial
proportion of the older population in two settings in north and
south India. Only 10% of those in the north and a quarter of those
in the south met the criteria for adequate levels. Our results are
relevant to current debates about the control of non-communica-
ble diseases in India. Low fruit and vegetable intake, tobacco use
and biomass fuels contribute respectively the third, fourth and fifth
ranked risk factors associated with mortality and disease burden in
India . Our results show that low dietary vitamin C intakes
(reflecting low fruit and vegetable intake), tobacco use and biomass
fuels are risk factors for vitamin C deficiency and add to the
evidence on the health consequences of these risk factors. In poor
communities, such as described in our study, consideration needs
to be given to measures to improve the consumption of vitamin C
rich foods and to discourage the use of tobacco. This includes a
raft of measures including agricultural and tobacco policy,
promoting awareness in communities through education and
employment of local dieticians. The growing proportion of older
people in India also highlights the importance of better
information on the nutritional status of this age group.
Conceived and designed the experiments: RDR AEF UC. Performed the
experiments: RDR PV SKG RJ NJ. Analyzed the data: AEF KEF.
Contributed reagents/materials/analysis tools: ISY. Wrote the paper: AF
RDR. Designed nutritional software for dietary data: RDR TR RJ.
Provided critical revisions of important intellectual content: ISY GM MC
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