| Literature DB >> 33889131 |
Chittari Venkata Harinarayan1,2, Harinarayan Akhila3, Edara Shanthisree1.
Abstract
Calcium and vitamin D are inseparable nutrients required for bone health. In the past half a century, the dietary calcium intake of rural, tribal, and urban India has declined. Though India is the largest producer of milk and cereals, the major source of calcium in India is through non-dairy products. The highest intake of cereals and lowest intake of milk & milk products was observed in rural and tribal subjects whereas, the intake of cereals, milk & milk products were similar in both urban and metropolitan subjects. One of the reasons for lower calcium intake was the proportion of calcium derived from dairy sources. Over the past half a century, the average 30-day consumption of cereals in the rural and urban population has declined by 30%. The Per Capita Cereal Consumption (PCCC)has declined despite sustained raise in Monthly Per capita Consumption Expenditure (MPCE) in both rural and urban households. The cereal consumption was the highest in the lowest income group, despite spending smaller portion of their income, as cereals were supplied through public distribution system (PDS). About 85% of the Indian population are vitamin D deficient despite abundant sunlight. Dietary calcium deficiency can cause secondary vitamin D deficiency. Though India as a nation is the largest producer of milk, there is profound shortage of calcium intake in the diet with all negative consequences on bone health. There is a decline in dietary calcium in the background of upward revision of RDI/RDA. There is a gap in the production-consumption-supply chain with respect to dietary calcium. To achieve a strong bone health across India, it is imperative to have population based strategies addressing different segments including supplementing dietary/supplemental calcium in ICDS, mid-day-meals scheme, public distribution system, educational strategies. Other measures like mass food fortification, biofortification, bioaddition, leveraging digital technologies, investments from corporate sector are some measures which can address this problem. India is a vast country with diverse social, cultural and dietary habits. No single measure can address this problem and requires a multi-pronged strategic approach to tackle the dietary calcium deficiency to achieve strong bone health while solving the problem of nutritional deficiency.Entities:
Keywords: Ragi (Eleusine coracana); dietary calcium deficiency; fortification; modern India; production supply consumption chain; recommended dietary allowances; recommended dietary intake; vitamin D
Mesh:
Substances:
Year: 2021 PMID: 33889131 PMCID: PMC8056136 DOI: 10.3389/fendo.2021.583654
Source DB: PubMed Journal: Front Endocrinol (Lausanne) ISSN: 1664-2392 Impact factor: 5.555
Figure 1Calcium-Vitamin D-PTH endocrine axis in health during calcium and/or vitamin D deprivation. PTH, Parathyroid Hormone, 20 HPT, secondary hyperparathyroidism, SPF, Skin Protection Factor.
Table depicting RDI of cereals, millets, milk and milk products, and RDA of calcium intake across various age groups in rural survey (22, 23) and tribal survey (24).
| GROUP | CEREALS & MILLETS | MILK & MILK PRODUCTS | CALCIUM INTAKE | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AVG INTAKE | RDI | <50% RDI | ≥70% RDI | AVG INTAKE | RDI | <50% RDI | ≥70% RDI | MEDIAN CAL INTAKE | RDA | <50% RDA | ≥70% RDA | |
|
| ||||||||||||
| 1–3 YRS | 131 | 175 | 33 | 49.6 | 86 | 300 | 80.8 | 12.4 | 166 | 600 | 74.1 | 15.5 |
| 4–6 YRS | 209 | 270 | 19.8 | 53.4 | 67 | 250 | 81.8 | 12.8 | 198 | 600 | 71 | 16.4 |
| 7–9 YRS | 262 | – | – | – | 64 | 226 | 600 | 66.8 | 18.6 | |||
| 10–12 GIRLS | 289 | 380 | 20 | 52.1 | 59 | 250 | 84.1 | 10.5 | 230 | 800 | 78.9 | 10.5 |
| 10–12 BOYS | 301 | 420 | 22.6 | 47.6 | 58 | 250 | 84.6 | 10.6 | 248 | 800 | 75.8 | 11.2 |
| 13–15 BOYS | 347 | – | – | – | 66 | – | – | – | 266 | 800 | 71 | 14.3 |
| 13–15 GIRLS | 324 | – | – | – | 58 | – | – | – | 249 | 800 | 74.7 | 12.3 |
| 16–17 BOYS | 386 | – | – | – | 74 | – | – | – | 299 | 800 | 66.8 | 17.4 |
| 16–17 GIRLS | 346 | – | – | – | 65 | – | – | – | 270 | 800 | 71.7 | 13.5 |
| WOMEN NPNL SED | 341 | 410 | 14.1 | 62.9 | 82 | 100 | 56.7 | 36 | 328 | 600 | 45.1 | 37.3 |
| WOMEN NPNL MOD | 391 | 440 | – | – | 73 | 150 | 292 | 600 | 52.2 | 28.9 | ||
| WOMEN PREG SED | 354 | – | – | – | 79 | – | – | – | 334 | 1200 | 76.1 | 7.5 |
| WOMEN PREG LACT | 395 | – | – | – | 66 | – | – | – | 327 | 1200 | 82.3 | 8.2 |
| MEN SED | 380 | 460 | 14.7 | 63 | 91 | 150 | 62.8 | 28.4 | 370 | 600 | 39.4 | 41.9 |
| MEN MODER | 444 | 520 | – | – | 78 | 200 | 335 | 600 | 43.3 | 36.4 | ||
| 60–69 YRS MEN* | 412 | 460 | <70% of RDI 48.4% | >70% of RDI 51.6% | 92 | 150 | <70% of RDI 74.3% | >70% of RDI 25.7% | 368 | 400 | <70% RDA 36.8% | >70% RDA 62.2% |
| 70–79 YRS MEN* | 374 | 460 | 73 | 150 | 338 | 400 | ||||||
| ≥80 YRS MEN* | 329 | 460 | 103 | 150 | 287 | 400 | ||||||
| 60–69 YRS WOMEN* | 337 | 420 | <70% of RDI 55% | >70% of RDI 45% | 76 | 100 | <70% of RDI 66.5% | >70% of RDI 33.5% | 290 | 400 | <70% RDA 49% | >70% RDA 51% |
| 70–79 YRS WOMEN* | 305 | 420 | 77 | 100 | 280 | 400 | ||||||
| ≥80 YRS WOMEN* | 251 | 420 | 76 | 100 | 254 | 400 | ||||||
|
| ||||||||||||
| 1–3 YRS | 149 | 175 | 20.1 | 61.9 | 16.6 | 300 | 97.3 | 1.4 | 95 | 400 | 79.9 | 10.6 |
| 4–6 YRS | 231.2 | 270 | 12.5 | 65.6 | 13.7 | 250 | 97.8 | 0.9 | 132 | 400 | 71.1 | 16.1 |
| 7–9 YRS | 289.1 | 14.5 | 159 | 400 | 63.3 | 21.4 | ||||||
| 10–12 BOYS | 331.6 | 420 | 15.2 | 59.7 | 16.1 | 250 | 97.1 | 1.3 | 171 | 600 | 75.7 | 14.2 |
| 10–12 GIRLS | 322.6 | 380 | 10.6 | 68.6 | 16.5 | 250 | 96.6 | 1.6 | 173 | 600 | 77.4 | 12.1 |
| 13–15 BOYS | 386.8 | 20.1 | 196 | 600 | 72.8 | 16.8 | ||||||
| 13–15 GIRLS | 359 | 16.1 | 179 | 600 | 74.6 | 15.3 | ||||||
| 16–17 BOYS | 440.1 | 22.2 | 213 | 500 | 69.3 | 19 | ||||||
| 16–17 GIRLS | 383.6 | 19 | 203 | 500 | 67.2 | 19.9 | ||||||
| WOMEN NPNL SED | 377.5 | 410 | 8.6 | 72.3 | 21 | 100 | 84.7 | 9.5 | 214 | 400 | 46.3 | 35.3 |
| WOMEN PREG SED | 388.2 | 26.7 | 204 | 1000 | 81 | 10.1 | ||||||
| WOMEN LACT SED | 436.4 | 16.5 | 230 | 1000 | 83.1 | 10.8 | ||||||
| MEN SED | 435.9 | 460 | 9.2 | 74.7 | 24.7 | 150 | 90.1 | 5.9 | 232 | 400 | 40.7 | 40.6 |
Rural Survey: Cereals and millets: About 49.6%–63% of them consumed >70% of the RDI according to their age and gender. About 14%–55% consumed <50% of the RDI. About 45%–52% of elderly adults, 60–≥80 years of age, consumed >70% of RDI. Milk & milk products: About 80%–85% of children of all age groups and 57%–63% of adults consumed <50% of the RDI. Only 10%–13% of children, 36% men, and 28% of women consumed >70% of the RDI for their age and gender. About 26% of men and 33.5% of women, between 60–≥80 years of age consumed >70% of RDI. RDA-Calcium: The median intake of calcium was less than RDA for their age and gender. About 67%–79% of children of various age groups, 40%–52% of women and men, 76%–82% of pregnant and lactating women consumed <50% of RDA. Only 10%–17% of children, 29%–42% of men and women;7.5%–8% of pregnant and lactating women consumed >70% of RDA. About 62% men and 51% of women between 60–≥80 years of age had intake of >70% of RDA.
Tribal survey: Cereals: About 60%–75% of them consumed >70% of the RDI for their age and gender. About 9%–20% consumed <50% of the RDI. Milk and milk products: About 85%–98% of children and adults consumed <50% of the RDI. Only 1%–9% of children, men and women consumed >70% of the RDI for their age and gender. RDA-Calcium: The median intake of calcium was less than RDA for their age and gender. About 63%–80% of children of various age groups, 40%–46% of men and women, 81%–83% pregnant and lactating women consumed <50% of RDA. About 10%–21% of children, 35%–40% of women and men, 10% of pregnant and lactating women consumed >70% of RDA.
*refers to data from ref (23).
Figure 2Rural survey () (22): (A) Distribution percent of children and adults according to daily intake of cereals & millets as percent of RDI. B Distribution percent of children and adults according to daily intake of milk & milk products as percent of RDI. (C) Distribution percent of children and adults according to daily intake of cereals & millets as percent of RDI in different states. children 1–3 years consumed >70% of RDI. The highest consumption of >70% of RDI was seen in Karnataka, MP, Orissa, 61%–65% in UP, 36%–45% in TN, AP, Gujarat, WB and only 19% in Kerala. Similar trend was seen in children with 4–6 years, 10–12 years boys & girls. More than 2/3 of men from Karnataka, AP, Gujarat, Orissa, UP consumed >70% of RDI of cereals & millets, 50-60% in TN, Maharashtra, WB and only 40% of subjects from Kerala. Similarly, >60% of women from TN, Karnataka, AP, Gujarat, MP, Orissa, UP consumed >70% of the RDI and the lowest was 31% from Kerala. (D) Distribution percent of children and adults according to daily intake of milk & milk products as percent of RDI in different states. 1–3 years children- 75-95% of children from Karnataka, AP, Gujarat, MP and Orissa consumed <50% of the RDI, except TN-with 53%. Less than 10% of children from the above states consumed >70% of RDI(TN-31.8%). Only 0.4% of children from Orissa consumed >70% of milk & milk products. Similar trend was seen in children 4–6 years, 10–12 years boys & girls. 65%–90% of men consumed <50% of RDI of milk & milk products. More than 70% of RDI consumption was seen in TN(53%), Gujarat(59%), Kerala(29%). (E) Average consumption of cereals & millets- Time trends showing a decline in consumption of cereals & millets by 20% in the past 4 decades. (F) Average consumption of milk & milk products- Time trends showing a decline in consumption of milk & milk products in the past 4 decades. (G) Graph depicting milk production and per capita availability for year 2011–2012. The consumption data of the rural survey for year 2011–2012 is superposed. Graph clearly depicts the low consumption of milk despite adequate availability. (H) Distribution of percent of children & adults–intake of calcium as percent of RDA. (I) Distribution of percent of children according to RDA of calcium in different states. Between 70%–85% of children, adolescent boys & girls of all the states have low calcium intake (<50% of RDA). Less than 15% of children (1–3 years) from Kerala, Karnataka, AP, Maharashtra, Gujarat, MP, Orissa, and 25%–30% of children from TN, WB and UP had intake of >70% of RDA. Similar pattern was seen in 4–6 years, 10–12 years boys & girls age group, only 10%–12% of subjects from all the states of age group 13–15 years boys & girls had an RDA of calcium >70%. (J) Distribution of percent of adults according to RDA of calcium in different states. Sedentary men-51 and 65% of subjects from TN, Gujarat and 25%–35% of subjects from AP, Maharashtra and Orissa had a calcium intake of >70% of RDA. Moderately active men->70% of RDA of calcium was met with by 35%–42% of the subjects from all states except Gujarat(50.8%), Maharashtra and WB (21%). Amongst the non-pregnant women 35%–45% of subjects from all states, except Gujarat (55%) and WB (27%), met with >70% of RDA of calcium. Uniformly, only 25%–35% of subjects of moderately active non-pregnant women met with adequate RDA of >70% with exception of Maharashtra (19%) and WB (16%). Less than 10% of pregnant women of all states except Kerala (21%) met with RDA limit of >70%. 65%–75% of them had RDA of <50% except Maharashtra (97%) and MP (96%). Similar scenario seen in lactating women. (K) Average calcium intake children time trends showing a decline in calcium intake over the past 4 decades. (L) Average calcium intake adults time trends showing a decline in calcium intake over the past 4 decades. RDI-Recommended Daily Dietary Intake; RDA-Recommended Daily Dietary Allowance; HH- Households; B-Boys; G-girls; WOMEN NPNL SED-women: non-pregnant, non-lactating and sedentary; WOMEN NPNL MOD-women: non-pregnant non-lactating and moderate; WOMEN PREG SED-women: pregnant and sedentary; WOMEN PREG LACT-women: pregnant and lactating; MEN SED-men: sedentary; MEN MOD-men: moderate; TN-Tamil Nadu; WB-West Bengal; MAHA-Maharashtra; KAR-Karnataka; AP-Andhra Pradesh; GUJ-Gujarat; MP-Madhya Pradesh; UP-Uttar Pradesh.
Table showing dietary calcium intake of different age groups and various study population across the country from 1999 to 2019.
| S.NO | PLACE | AGE YRS | n | STUDY POPU | STUDY TYPE | CALCIUM INTAKE MG/DAY | YR OF STUDY | REF |
|---|---|---|---|---|---|---|---|---|
|
| PUNE | 8.4 ± 1.1 | 79 | VITAMIN D GROUP | VIT D INTERVENTION STUDY | 188 ± 56 | 2019 | ( |
|
| PUNE | 7.9 ± 1.2 | 99 | NON VITAMIN D GROUP | VIT D INTERVENTION STUDY | 207 ± 54 | 2019 | ( |
|
| PUNE | 8 ± 1.2 | 192 | GOVT PRIMARY SCHOOL BOYS | CROSS SECTI | 216 ± 69 | 2018 | ( |
|
| PUNE | 7.9 ± 1.1 | 167 | GOVT PRIMARY SCHOOL GIRLS | CROSS SECTI | 194 ± 49 | 2018 | ( |
|
| BANGALORE | 59.05 ± 12.61 | 252 | TERTIARY CARE HOSP | CROSS SECTI | 499.94 | 2018 | ( |
|
| KOKAN REGION | MEDIAN 14 | 80 | ADOLOSCENT SCHOOL GIRLS | CROSS SECTI | MEDIAN-189.4(MIN-49.1,MAX-701.6) | 2018 | ( |
|
| MUMBAI | 36.50 ± 2.74 | 265 | GROUP-1(NORMAL BMD)SLUM DWELLERS | CROSS SECTI | 214 ± 176 | 2018 | ( |
|
| MUMBAI | 37.5 ± 3.44 | 1135 | GROUP-2(LOW BMD) SLUM DWELLERS | CROSS SECTI | 301 ± 158 | 2018 | ( |
|
| PUNE | 2–16 | 220 | WHEAT MILK PATTERN DIET | INTERVENTION STUDY | 479 ± 222 | 2017 | ( |
|
| PUNE | 2–16 | 220 | RICE PROTEIN PATTERN DIET | INTERVENTION STUDY | 351 ± 196 | 2017 | ( |
|
| PATAN, GUJARAT | 12 ± 1.1 | 30 | LOWER SES | CROSS SECTIONAL SEMI URBAN REGION | 441.2 ± 227.6 | 2017 | ( |
|
| PATAN, GUJARAT | 11.7 ± 0.5 | 30 | MIDDLE SES | CROSS SECTIONAL SEMI URBAN REGION | 484.3 ± 160.9 | 2017 | ( |
|
| PATAN, GUJARAT | 12 ± 1.2 | 30 | UPPER SES | CROSS SECTIONAL SEMI URBAN REGION | 749.2 ± 245.4 | 2017 | ( |
|
| DELHI | 28.5 ± 10.40 | 88 | OUTDOOR WORKERS | CROSS SECTI | 405 | 2016 | ( |
|
| DELHI | 25.8 ± 6.7 | 32 | MIXED GROUP | CROSS SECTI | 438 | 2016 | ( |
|
| DELHI | 31.7 ± 10.07 | 74 | INDOOR WORKERS | CROSS SECTI | 512 | 2016 | ( |
|
| PUNE | 27.7 ± 3.5 | 128 | MOTHERS-7 DAYS POSTPARTUM | CROSS SECTI | 949 ± 340 | 2016 | ( |
|
| PUNE | 29.4 ± 3.2 | 88 | MOTHERS WITH CHILDREN 1YR AGE | CROSS SECTI | 618 ± 256 | 2016 | ( |
|
| PUNE | 29.3 ± 3.0 | 84 | MOTHERS WITH CHILDREN 3YR AGE | CROSS SECTI | 530 ± 181 | 2016 | ( |
|
| BALLABGARH, HARYANA | 217 | >28-36 WK PREG | CROSS SECTI | 858.4 + 377 | 2016 | ( | |
|
| TIRUPATI | 40 ± 0.9(MEAN + SEM) | 325 | RURAL | CROSS SECTI | 269 ± 2(MEAN | 2015 | ( |
|
| TIRUPATI | 47 ± 0.6(MEAN + SEM) | 508 | URBAN | CROSS SECTI | 308 ± 2.3(MEAN + SEM) | 2015 | ( |
|
| TIRUPATI | 43 ± 0.7(MEAN + SEM) | 524 | METRO | CROSS SECTI | 526 ± 8(MEAN + SEM) | 2015 | ( |
|
| VELLORE | 58(RANGE:40–74) | 106 | ERODE TN | CROSS SECTI | 632.72 ± 28.23 | 2015 | ( |
|
| DELHI | 23.4 ± 3.9 | 178 | PREGNANT WOMEN | CROSS SECTI | 568.0 ± 370.2 | 2015 | ( |
|
| DELHI | 24.7 ± 4.36 | 158 | IMMEDIATE POSTPARTUM WOMEN | CROSS SECTI | 634 ± 441 | 2015 | ( |
|
| MUMBAI | 43.21 ± 4.16 | 76 | MALE BMD:Z SCORE>2-NORMAL BMD | COMMU HEALTH CAMP | 782 | 2014 | ( |
|
| MUMBAI | 39.09 ± 4.02 | 80 | FEMALE BMD : ZSCORE>2-NORMAL BMD | COMMU HEALTH CAMP | 590 | 2014 | ( |
|
| MUMBAI | 42 ± 4.42 | 21 | MALE BMD:Z SCORE<2-LOW BMD | COMMU HEALTH CAMP | 715 | 2014 | ( |
|
| MUMBAI | 40.53 ± 4.86 | 17 | FEMALE BMD : ZSCORE<2-LOW BMD | COMMU HEALTH CAMP | 514 | 2014 | ( |
|
| ANDHRA (NEAR HYDERABAD) | 20.44 ± 1.22 | 465 | VILLAGE WOMEN | CROSS SECTI | 423.8(405, 443.5) 95%CI | 2014 | ( |
|
| ANDHRA (NEAR HYDERABAD) | 20.2 ± 1.2 | 981 | VILLAGE MEN | CROSS SECTI | 618.7(600.3, 637.6)95%CI | 2014 | ( |
|
| ICDS VILLAGES | 9 months-Control group | 176 | ICDS PROJECT VILLAGES | INTERVENTION STUDY | 77(14, 177)-MEDIAN(CI25,75) | 2014 | ( |
|
| ICDS VILLAGES | 9 months-Complimentary Feeding | 177 | ICDS PROJECT VILLAGES | INTERVENTION STUDY | 127(44, 245)-MEDIAN(CI25,75) | 2014 | ( |
|
| ICDS VILLAGES | 9 months-Responsive Complementary Feeding and Play Group (RCF&PG) | 158 | ICDS PROJECT VILLAGES | INTERVENTION STUDY | 127(44, 235)-MEDIAN(CI25,75) | 2014 | ( |
|
| ACROSS INDIA | 41.2 + 10.2-VEGETARIANS | 2148 | INDIAN MIGRATION STUDY(IMS) | QUESTIONNARIE SURVEY | 980.6(751–1247.1)-MEDIAN(IQR) | 2014 | ( |
|
| ACROSS INDIA | 40.8 + 10.4 NON-VEGETARIANS | 4407 | INDIAN MIGRATION STUDY(IMS) | QUESTIONNARIE SURVEY | 946.5(692.9–1253.1)-MEDIAN(IQR) | 2014 | ( |
|
| NORTH INDIA TERTIARY CARE CENTRE | 6 MONTHS to 5 YRS | 67 | CHILDREN WITH RICKETS | RANDOMIZED CONTROLLED TRAIL | 204 ± 129 | 2013 | ( |
|
| KASHMIR | 28.75 | 64 | MEN | CROSS SECTI | 368 ± 98.4 | 2012 | ( |
|
| KASHMIR | 26.79 | 28 | WOMEN | CROSS SECTI | 284.4 ± 70.8 | 2012 | ( |
|
| MUMBAI | 25–35 | 1137 | TERITIARY CARE-WESTERN INDIA | CROSS SECTI | 322.92 ± 135.17 | 2011 | ( |
|
| DELHI | 18.7 ± 1.2 | 90 | COLL STUDENTS SPORTS GIRLS | CROSS SECTI | 779.1 ± 324.5 | 2011 | ( |
|
| DELHI | NA | 96 | COLL STUDENTS CONTROLS | CROSS SECTI | 409.7 ± 172.5 | 2011 | ( |
|
| CHANDIGARH | 19.4 | 329 | COLLEGE STUDENTS SUMMER | CROSS SECTI | 625.5 ± 273 | 2011 | ( |
|
| CHANDIGARH | 19.4 | 237 | COLLEGE STUDENTS WINTER | CROSS SECTI | 662.6 ± 215 | 2011 | ( |
|
| PUNE | 2.9 ± 0.5 TODDLERS | 30 | study LOCAL CRECHE OF UNDERPRIVILEG MOTHERS | INTERVENTION | 172 ± 82 | 2011 | ( |
|
| PUNE | 2.6 ± 0.5 TODDLERS | 28 | study LOCAL CRECHE OF UNDERPRIVILEG MOTHERS | INTERVENTION | 217 ± 111 | 2011 | ( |
|
| PUNE | 14.1(13.8–14.5)MEDIAN(25%–75%ILE) | 100 | USES-BOYS | CROSS SECTI | 893(689–1295)-MEDIAN(25%–75%ILE) | 2010 | ( |
|
| PUNE | 14.4(13.8–15.2)MEDIAN(25%–75%ILE) | 100 | LSES-BOYS | CROSS SECTI | 767(585–1043)-MEDIAN(25%–75%ILE) | 2010 | ( |
|
| PUNE | 14.7(14.4–14.9)MEDIAN(25%–75%ILE) | 100 | USES-GIRLS | CROSS SECTI | 764(541–959)-MEDIAN(25%–75%ILE) | 2010 | ( |
|
| PUNE | 14.5(14.0–15.1)MEDIAN(25%–75%ILE) | 100 | LSES-GIRLS | CROSS SECTI | 506(380–674)-MEDIAN(25%–75%ILE) | 2010 | ( |
|
| DELHI | 12.0 ± 2.8 | 60 | LSES-2 MONTHLY GROUP | VIT D SUPPL STUDY | 480.8 | 2010 | ( |
|
| DELHI | 11.4 ± 3.0 | 64 | LSES-MONTHLY GROUP | VIT D SUPPL STUDY | 456.3 | 2010 | ( |
|
| DELHI | 11.6 ± 2.7 | 81 | USES-2 MONTHLY GROUP | VIT D SUPPL STUDY | 707.3 | 2010 | ( |
|
| DELHI | 11.7 ± 2.8 | 85 | USES-MONTHLY GROUP | VIT D SUPPL STUDY | 670.5 | 2010 | ( |
|
| DELHI | 12.4 | 193 | LSES | CROSS SECTI | 454.2 | 2008 | ( |
|
| DELHI | 12.3 | 211 | USES | CROSS SECTI | 685.5 | 2008 | ( |
|
| DELHI | 34 ± 13.1 | 28 | APPARENTLY HEALTHY SUBJECTS | CROSS SECTI | 650 | 2008 | ( |
|
| AGOTA VILLAGE,UP | 42.8 | 32 | RURAL MALE | CROSS SECTI | 905 | 2008 | ( |
|
| AGOTA VILLAGE,UP | 43.4 | 25 | RURAL FEMALE | CROSS SECTI | 595 | 2008 | ( |
|
| TIRUPATI | 46 | 32 | URBAN-MALE | CROSS SECTI | 323 | 2007 | ( |
|
| TIRUPATI | 43 | 109 | RURAL-MALE | CROSS SECTI | 271 | 2007 | ( |
|
| TIRUPATI | 46 | 476 | URBAN-FEMALE | CROSS SECTI | 306 | 2007 | ( |
|
| TIRUPATI | 43 | 96 | RURAL-FEMALE | CROSS SECTI | 262 | 2007 | ( |
|
| PUNE | 27.5(IQR 25.6, 29.6) | 690 | WOMEN PREG 18 WK GA | CROSS SECTI | 274-MEDIAN(IQR 223, 354) | 2006 | ( |
|
| PUNE | 27.5(IQR 25.6, 29.6) | 667 | WOMEN PREG 28 WK GA | CROSS SECTI | 268-MEDIAN(IQR 208, 332) | 2006 | ( |
|
| TIRUPATI | 59.5 | 164 | POST MENOPAU | CROSS SECTI | 323 | 2005 | ( |
|
| LUCKNOW | 20–29 | 140 | PREG WOMEN URBAN | VILLAGES AROUND | 842 | 2005 | ( |
|
| LUCKNOW | 20–29 | 67 | PREG WOMEN RURAL | VILLAGES AROUND | 549 | 2005 | ( |
|
| BARABANKI DIST,LUCKNOW | 14·3 ± 2·7 | 121 | ADOL GIRLS | CROSS SECTI | 211 ± 158 | 2005 | ( |
|
| BARABANKI DIST,LUCKNOW | 26·7 ± 4·1 | 139 | PREG | CROSS SECTI | 214 ± 150 | 2005 | ( |
|
| LUCKNOW | 6.5 ± 1.2 | 15 | GROUP 1: NOT RECEIVING CAL/VIT D SUPPLI | IDIOPATHIC NEPHROTIC SYNDROME | 696.7 ± 73.5 | 2005 | ( |
|
| LUCKNOW | 5.3 ± 0.55 | 73 | GROUP 2:RECEIVING CAL/VIT D SUPPLI | IDIOPATHIC NEPHROTIC SYNDROME | 723.3 ± 35.2 | 2005 | ( |
|
| TIRUPATI | 44 | 191 | RURAL | CROSS SECTI | 264 | 2004 | ( |
|
| TIRUPATI | 45.5 | 125 | URBAN | CROSS SECTI | 356 | 2004 | ( |
|
| LUCKNOW | 16.2 | 21 | SUBJECTS OF OPD | CROSS SECTI | 265 | 2003 | ( |
|
| DELHI | 22.7 | 40 | MEN INDIAN PARAMILITARY FORCES | CROSS SECTI | 1041 | 2003 | ( |
|
| DELHI | 23.4 | 50 | WOMEN INDIAN PARAMILITARY FORCES | CROSS SECTI | 764.8 | 2003 | ( |
|
| DELHI | 25 ± 5 MALE | 31 | SOLIDER-WINTER | CROSS SECTI | 1104 ± 666 | 2000 | ( |
|
| DELHI | 23 ± 5 (M:F-11:8) | 19 | PHYSICIANS & NURSES-WINTER | CROSS SECTI | 879 ± 165 | 2000 | ( |
|
| DELHI | 43 ± 16(M:F-10:5) | 15 | DEPIGMENTED PERSONS-WINTER | CROSS SECTI | 980 ± 300 | 2000 | ( |
|
| DELHI | 24 ± 4(M:F-11:8) | 19 | PHYSICIANS & NURSES-SUMMER | CROSS SECTI | 879 ± 165 | 2000 | ( |
|
| DELHI | 23 ± 3 | 29 | PREG WOMEN-SUMMER-LSES | CROSS SECTI | 345 ± 78 | 2000 | ( |
|
| ALWAR & BHARATPUR RAJASTHAN | 6–<12 MONTHS | 16 | PROSPECTIVE STUDY | 514.2 ± 413 | 1999 | ( | |
|
| ALWAR & BHARATPUR RAJASTHAN | 12–35 MONTHS | 31 | PROSPECTIVE STUDY | 393 ± 332.5 | 1999 | ( | |
|
| ALWAR & BHARATPUR RAJASTHAN | 36–72 MONTHS | 13 | PROSPECTIVE STUDY | 209.7 ± 135 | 1999 | ( | |
All values are mean ± SD unless stated. LSES-lower socioeconomic status; USES-upper socioeconomic status; PREG-pregnancy; WK-weeks; GA-gestational age; GOVT-government; BMD-bone mineral density; ADOL-adolescent; SES-socioeconomic status; UP-Uttar Pradesh; ICDS-integrated child development services; SEM-Standard Error Of Mean; IQR-interquartile range; MIN-minimum; MAX- maximum; YRS-years; CROSS SECTI-cross sectional survey; COMMU HEALTH CAMP- community health camp.
Figure 3Tribal survey ( ) (24): (A) Distribution percent of children & adults according to daily intake of cereals & millets as percentage of RDI. (B) Distribution percent of children & adults according to daily intake of milk & milk products as percentage of RDI. (C) Distribution percent of children & adults according to daily intake of cereals & millets as percent of RDI- different states. About 60%–76% of Children 1–3 years from AP, Maharashtra, MP, WB, Orissa, consumed >70% of RDI with maximum from Gujarat(82%) and minimum from Kerala(36%). More than 45%–86% of children 4–6 years consumed >70% of RDI with exception of Kerala(27%). Among children of 10–12 years boys & girls, >70% of RDI was consumed from Orissa (88% & 93%) WB (85% & 90%) and least from Kerala(16% & 22%) respectively. In remaining states, consumption ranges from 35% to 68% for boys and 42% to 77% for girls. More than 51%–96% of adult men consumed >70% of RDI for cereals & millets from all states. The highest being MP (82%), WB (92%), and Orissa (96%). Similar scenario was seen with non-pregnant women. (D) Distribution percent of children & adults according to daily intake of milk & milk products as percent of RDI- different states. Uniformly, 80%–95% of population consumed <50% of RDI of milk & milk products among all age groups in all states. (E) Average intake of cereals & millets-Time trends showing a decline in intake of cereals & millets amongst all age groups in all states. (F) Average intake of milk & milk products-Time trends showing a decline in intake of milk & milk products across all age groups in all states. (G) Graph depicting the milk production and per capita availability for the year 2007–2008. The consumption data of the tribal survey for the year 2007–2008 is superposed. Graph clearly depicts the low consumption of milk despite adequate availability. (H) Distribution of percent of children intake of calcium as percent of RDA. (I) Distribution of percent of adults’ intake of calcium as percent of RDA. (J) Distribution of percent of children according to RDA of calcium in different states. Among children of 1–3 years age, about 80%–90% of HH had intake of calcium <50% of RDA and only ~10% of HH had >70% of RDA. Similar scenario was seen in children 4–6 years of age. Among children of 7–9 years of age, two-thirds of HH had daily intake of calcium <50% of RDA and only 20% of HH had >70% of RDA. Among 10–12 years boys & girls, 70%–85% of HH consumed <50% of RDA of calcium [except Orissa-43%] and less than 15% of HH achieved the criteria of >70% RDA of calcium[Orissa-37%]. Similar scenario was seen in age group of 13–15 years and 16–17 years boys & girls. (K). Distribution of percent of adults according to RDA of calcium in different states. Amongst sedentary men, 35%–45% of the HH from all the states achieved >70% of RDA of calcium with exception of MP (20%) and Orissa (55%). About 35%–45% of HH of all the states had an RDA of <50% with exception of MP (60%) and Orissa (31%). Similar scenario was seen amongst non-pregnant, sedentary women. Only <10% of the HH of pregnant women from all states (except karnataka-25%,Orissa 21%) had >70% RDA of calcium. Almost 85%–90% of HH of pregnant women had calcium intake of <50% in all states. Similar scenario was seen amongst lactating women. (L) Average calcium intake—time trends showing a decline in dietary calcium intake across all age groups over the past four decades. RDI-Recommended Daily Dietary Intake; RDA-Recommended Daily Dietary Allowance; HH-Households; B-Boys; G-girls; WOMEN NPNL SED-women: nonpregnant, non-lactating and sedentary; WOMEN NPNL MOD-women: non-pregnant non-lactating and moderate; WOMEN PREG SED-women: pregnant and sedentary; WOMEN PREG LACT-women: pregnant and lactating; MEN SED-men: sedentary; MEN MOD-men: moderate; TN-Tamil Nadu; WB-West Bengal; MAHA-Maharashtra; KAR-Karnataka; AP-Andhra Pradesh; GUJ-Gujarat; MP-Madhya Pradesh; UP-Uttar Pradesh.
(104, 105) The daily intake of various food categories in grams per capita per day and nutrients in grams per consumer unit in different states in India[Precision is > 0.05 happens due to low coverage/sample size or high coefficient of variation (SD/Mean) or both].
| CALCIUM | MILK CONSUP | ALL CEREALS | RICE | WHEAT | RAGI & ITS PRODUCTS | JOWAR & ITS PRODUCTS | BAJRA & ITS PRODUCTS | MAIZE & ITS PRODUCTS | ||
|---|---|---|---|---|---|---|---|---|---|---|
|
| mean ± SD (median) | mean ± SD (median) | mean ± SD (median) | mean ± SD (median) | mean ± SD (median) | mean ± SD | mean ± SD | mean ± SD | mean ± SD | |
| 1 | Andaman & Nicobar Island | 484 ± 242(428) | 73 ± 119(10) | 396 ± 112(395) | 322 ± 121(320) | 56 ± 43(59) | 0 | 0 | 0 | 0 |
| 2 | Andhra Pradesh | 463 ± 202(421) | 175 ± 125(147) | 443 ± 121(438) | 401 ± 120(399) | 12 ± 16(9) | 7.127 ± 19.954[0] | 5.518 ± 18.609[1] | 0.268 ± 4.634[1] | 0.043 ± 0.782[1] |
| 3 | Arunachal Pradesh | 258 ± 170(217) | 48 ± 99(3) | 497 ± 208(468) | 441 ± 196(418) | 17 ± 35(0) | 0.016 ± 1.445[1] | 0.167 ± 1.846[1] | 0.034 ± 1.678[1] | 11.795 ± 36.575[1] |
| 4 | Assam | 250 ± 125(224) | 60 ± 67(46) | 483 ± 114(468) | 446 ± 118(436) | 21 ± 37(13) | 0 | 0 | 0 | 0.036 ± 0.953[1] |
| 5 | Bihar | 424 ± 187(392) | 168 ± 130(149) | 489 ± 121(474) | 244 ± 74(233) | 224 ± 70(217) | 0.006 ± 0.859[1] | 0.000 ± 0.066[1] | 0.176 ± 2.716[1] | 4.202 ± 15.852[1] |
| 6 | Chandigarh | 682 ± 302(620) | 368 ± 213(314) | 296 ± 94(288) | 69 ± 53(49) | 218 ± 78(215) | 0 | 0 | 0 | 0.314 ± 2.814[1] |
| 7 | Chhattisgarh | 254 ± 156(212) | 48 ± 96(0) | 489 ± 122(476) | 433 ± 132(432) | 46 ± 53(34) | 0.002 ± 0.138[1] | 0.063 ± 0.839[1] | 0 | 1.540 ± 8.685[1] |
| 8 | Dadra & Nagar Havelli | 348 ± 254(238) | 111 ± 166(49) | 324 ± 85(333) | 226 ± 122(272) | 71 ± 98(11) | 4.616 ± 15.636[1] | 2.978 ± 13.924[1] | 2.243 ± 12.581[1] | 0 |
| 9 | Daman & Diu | 486 ± 154(448) | 168 ± 105(143) | 311 ± 73(314) | 148 ± 63(144) | 101 ± 81(85) | 0 | 18.663 ± 38.160[1] | 15.583 ± 29.470[1] | 0 |
| 10 | Goa | 453 ± 206(428) | 206 ± 138(201) | 341 ± 76(332) | 250 ± 63(247) | 57 ± 40(51) | 0.477 ± 3.631[1] | 2.518 ± 14.646[1] | 0 | 0 |
| 11 | Gujarat | 556 ± 231(524) | 254 ± 164(226) | 334 ± 101(331) | 77 ± 63(59) | 162 ± 88(167) | 1.072 ± 11.538[1] | 8.042 ± 30.422[1] | 50.942 ± 84.274[0] | 24.374 ± 72.419[1] |
| 12 | Haryana |
|
| 357 ± 92(351) | 34 ± 37(24) | 315 ± 90(310) | 0 | 0.014 ± 0.486[1] | 3.140 ± 16.877[1] | 0.485 ± 3.476[1] |
| 13 | Himachal Pradesh | 717 ± 374(633) | 388 ± 295(313) | 472 ± 93(468) | 175 ± 69(176) | 258 ± 70(257) | 0 | 0.029 ± 2.063[1] | 0.265 ± 5.909[1] |
|
| 14 | Jammu & Kashmir | 640 ± 282(571) | 351 ± 198(312) | 492 ± 125(467) | 314 ± 169(286) | 133 ± 101(126) | 0 | 0.108 ± 3.115[1] | 0.040 ± 1.915[1] | 25.336 ± 56.174[0] |
| 15 | Jharkhand | 344 ± 219(270) | 110 ± 145(37) | 493 ± 128(491) | 343 ± 135(324) | 131 ± 96(132) | 0 | 0.035 ± 1.520[1] | 0.011 ± 0.456[1] | 3.471 ± 15.881[1] |
| 16 | Karnataka | 577 ± 307(500) | 170 ± 117(143) | 375 ± 105(369) | 221 ± 90(211) | 40 ± 31(33) |
|
| 2.417 ± 22.504[1] | 0.510 ± 4.793[1] |
| 17 | Kerala | 439 ± 220(392) | 132 ± 128(109) | 357 ± 107(347) | 284 ± 89(278) | 31 ± 27(26) | 0.296 ± 2.045[1] | 0.026 ± 0.970[1] | 0.002 ± 0.091[1] | 0.021 ± 0.760[1] |
| 18 | Lakshadweep | 346 ± 133(328) | 16 ± 29(10) | 408 ± 111(418) | 331 ± 99(330) | 32 ± 24(30) | 0 | 0 | 0 | 0 |
| 19 | Madhya Pradesh | 456 ± 239(410) | 180 ± 166(142) | 459 ± 130(448) | 86 ± 94(44) | 342 ± 147(338) | 0.001 ± 0.057[1] | 5.024 ± 41.985[1] | 0.147 ± 11.277[1] | 16.951 ± 66.779[1] |
| 20 | Maharashtra | 453 ± 200(423) | 165 ± 129(141) | 372 ± 109(374) | 123 ± 82(105) | 169 ± 84(164) | 1.116 ± 12.113[1] | 38.941 ± 62.621[0] | 15.007 ± 40.387[0] | 0.496 ± 6.969[1] |
| 21 | Manipur | 183 ± 76(167) | 18 ± 38(3) |
|
| 1 ± 10(0) | 0 | 0 | 0 | 0.044 ± 0.661[1] |
| 22 | Meghalaya | 235 ± 114(221) | 52 ± 61(34) | 405 ± 64(400) | 377 ± 65(375) | 9 ± 17(0) | 0 | 0 | 0 | 1.075 ± 5.976[1] |
| 23 | Mizoram | 273 ± 158(215) | 55 ± 83(8) | 500 ± 121(489) | 484 ± 118(476) | 4 ± 25(0) | 0 | 0 | 0.008 ± 0.355[1] | 3.224 ± 15.081[1] |
| 24 | Nagaland | 217 ± 90(206) | 20 ± 40(11) | 491 ± 83(491) | 476 ± 88(482) | 3 ± 21(0) | 0 | 0 | 0 | 3.552 ± 16.885[1] |
| 25 | NCT of Delhi | 651 ± 262(615) | 329 ± 178(298) | 305 ± 92(304) | 76 ± 43(70) | 214 ± 82(214) | 0 | 0 | 0.014 ± 0.424[1] | 0.329 ± 2.606[1] |
| 26 | Puducherry | 590 ± 220(569) | 246 ± 139(242) | 368 ± 109(360) | 309 ± 100(300) | 36 ± 25(36) | 1.768 ± 6.043[1] | 0 | 0.009 ± 0.270[1] | 0.009 ± 0.207[1] |
| 27 | Punjab | 823 ± 367(753) | 469 ± 282(412) | 353 ± 83(346) | 37 ± 39(27) | 307 ± 83(301) | 0 | 0.006 ± 0.347[1] | 0.028 ± 0.493[1] | 4.394 ± 13.683[1] |
| 28 | Rajasthan | 713 ± 355(641) | 380 ± 275(312) | 460 ± 112(449) | 12 ± 17(8) |
| 0.001 ± 0.067[1] | 0.890 ± 18.567[1] |
| 11.463 ± 47.453[1] |
| 29 | Sikkim | 497 ± 183(485) | 255 ± 138(258) | 408 ± 96(406) | 354 ± 92(356) | 25 ± 21(22) | 0 | 0 | 0 | 6.852 ± 17.477[1] |
| 30 | Tamil Nadu | 466 ± 202(433) | 181 ± 128(157) | 359 ± 102(352) | 320 ± 103(313) | 23 ± 24(19) | 3.568 ± 12.820[0] | 0.146 ± 2.540[1] | 0.151 ± 2.509[1] | 0.081 ± 1.499[1] |
| 31 | Telangana | 407 ± 171(382) | 155 ± 106(134) | 451 ± 115(444) | 405 ± 115(401) | 21 ± 25(15) | 0.358 ± 2.501[1] | 12.509 ± 35.192[1] | 0.011 ± 0.417[1] | 0.138 ± 2.076[1] |
| 32 | Tripura | 291 ± 131(257) | 49 ± 80(3) | 548 ± 108(540) | 521 ± 106(515) | 8 ± 15(0) | 0 | 0 | 0 | 0.138 ± 2.358[1] |
| 33 | Uttar Pradesh | 501 ± 286(427) | 220 ± 215(168) | 450 ± 116(442) | 155 ± 97(159) | 285 ± 102(269) | 0 | 0.131 ± 4.972[1] | 1.354 ± 12.830[1] | 0.894 ± 7.937[1] |
| 34 | Uttarakhand | 649 ± 296(598) | 308 ± 208(269) | 481 ± 106(474) | 190 ± 74(183) | 276 ± 77(272) | 4.033 ± 13.791[1] | 0.002 ± 0.167[1] | 0 | 0.432 ± 5.292[1] |
| 35 | West Bengal | 321 ± 163(282) | 72 ± 95(39) | 450 ± 122(442) | 354 ± 134(349) | 66 ± 56(54) | 0.000 ± 0.189[1] | 0.000 ± 0.024[0] | 0.000 ± 0.031[0] | 0.070 ± 1.640[1] |
| 36 | Odisha | 282 ± 155(237) | 60 ± 94(5) | 526 ± 124(519) | 468 ± 137(465) | 33 ± 45(16) | 1.578 ± 8.559[1] | 0.040 ± 1.299[1] | 0.050 ± 2.295[1] | 0.401 ± 4.931[1] |
Bold values indicate- highest daily intake of various food categories in different states.
Table showing strategies to combat dietary calcium deficiency governmental and digital in rural and urban region.
| S.NO | Program | TARGET POPULATION | FEATURES | IMPACT | LIMITATIONS | REMEDIAL MEASURES |
|---|---|---|---|---|---|---|
| 1 |
| |||||
| a) Integrated Child Development program (ICDS) | Community level | Food supplement at community level | Reduced school dropouts | Did not help achieving nutrition sufficiency | Instant or precooked fortified products for infants and children can be given: complementary food supplements, micronutrient powders(can be used as home fortificants or point-of-use fortificants) and fortified blended foods. Cookies, biscuits, compressed bars and chikkies are other type of fortified complimentary foods that can be used. | |
| b) National Guidelines for Calcium Supplementation during Pregnancy and Lactation | Pregnant women from 1st trimester till 6 months post-partum | 500 mg elemental calcium and 250 IU Vitamin D3
| Increase in awareness of nutrition during and after pregnancy | Calcium and Vitamin D dose advocated is far less than the guidelines for treatment deficiency for population at risk ( | 1) Upgrade vitamin D and calcium dose. | |
| c) Mid–Day–Meals Scheme (MDM) | 1) Primary stage (class 1–5). | Nutrition norm: 1) primary stage - 450 calories. | Increase in school going children with 25 crore children studying in 15 lakh schools | 1) In year 2018–2019, there was 25% gap in coverage ( | 1) Educate parent and children. | |
| d) Targeted public distribution system | 1) Below Poverty Line(BPL)(to the poorest families), 2) | |||||
|
| 1) Lower socio economic strata | 1) Involve ISKON, Akshaya Patra, | ||||
|
| Discussed in our previous review ( | |||||
|
| Growing children, pregnant and lactating mothers, health conscious population, | Fortification of milk, flour, salt oil etc. | ||||
| 2. |
| It can deliver significant proportion of RDA for a number of micro nutrients without necessitating a change in dietary pattern of the population on a continuous basis and without calling for individual compliance | Cannot correct all or either of severity of micro nutrient deficiency, locality or poverty limiting the access of the FF | This problem is overcome by the PDS which caters to 80 crore population | ||
| a) Home fortification (HF) | At Household level | Encourages self-reliance, distributes cost effectively and widely, allows freedom of individual choice to utilize the additives | 1) No guarantee the target population would participate, 2) The supply of additives has to be replenished to sustain HF, 3) Uncomfortable feel of adding a substance to their food without knowing what it is and |
Overcome by educational programs ( | ||
| b) Commercial and industrial fortification (IF) | reaches large populations through PDS or retail stores | Can be made available at low costs with high quantity of production | The producer may drastically increase the price or some may unknowingly perceive the addition as unethical practice. | Overcome by legislation ( | ||
| c) Biofortification (BF) (genetically modified) | can benefit large population | Well suited for daily diet of low income population using large staple foods. | it requires minimal intervention, is highly sustainable once it is introduced, |
Improper knowledge may impact the mono cultures and reduce the bioavailability | Overcome by educational programs | |
Table showing strategies to combat dietary calcium deficiency governmental and digital in rural and urban region.
| Solutions/Approaches for Rural Regions. | |
|---|---|
|
| •Educate the community about the nutritious food through broadcast on digital channels. Program aired on Vande Gujarat Channel-1 and streamed through YouTube/Facebook has nutrition experts providing guidance through digital channels ( |
| •Deliver educational content in classrooms, availability of educational games in the mobile apps and television programs can shift the attitude towards consuming of nutrient rich food ( | |
| •Drawing parallels from the agriculture industry where mobile phones are used as a fast and easy access to communicate and deliver information ( | |
|
| •Information about importance of nutrition rich food through educational toys for children, targeted advertisements by the local community and local governance bodies helping to increase awareness and availability of calcium rich foods. |
| •To address the problem of digital exclusion among marginalized communities and to educate them of importance of calcium rich diet, verbal education about importance of strong bone health can be delivered through local nutrition experts or Anganwadi workers. This can also be taken up at the public distribution centers for cereals and grains. | |
|
| •Aadhar-based milk banks can also be set-up, wherein IoT-based scanners can be used to scan card and provide milk supply twice a day for each person which will need to be consumed immediately. |
|
| |
|
| •Technology solutions act as a guidance for self-management of adequate intake of nutrient rich food including calcium for bone health. There are many mobile apps available to track the calcium intake in the daily diet. The mobile apps inputs information of the user’s daily intake of calcium through recall, which is used to estimate the gap between daily intake and RDA, thereby suggesting the additional intake required based on RDI. These apps provide basic information and needs to be built for a holistic approach of providing personalized service including periodic monitoring. |
|
| •There are many apps available based on analytics and artificial intelligence (AI) to help users maintain nutritious and balanced diet. These apps use predictive analytics, artificial intelligence and natural language processing to help track and monitor nutrition intake ( |
| •Nestle India has launched artificial intelligence (AI) based nutrition assistant with a voice-activated functionality which responds to nutrition queries. •Nestlé India Nutrition Assistant (NINA), built in association with Google, focuses on parents and caregivers of children up to 12 years of age and suggests custom meal plans personalized to user preferences. AI fuels automated learning system in the app and drives self-learning as the usage of the app increases ( | |
|
| •In India, there is a need for industry endorsed calcium management apps which allows self-tracking of calcium intake through periodic recording of food and nutrient intake as well as risk assessment. |
| •There are many computer-based tools available for guided dietary intake of nutrition which can also be used for bringing the awareness and importance of calcium intake for bone health. It has been proven that computer-based self-management tools for calcium intake has led to higher level of calcium intake over a period of time ( | |