| Literature DB >> 28327512 |
Ryan Eyn Kidd Man1, Ling-Jun Li2, Ching-Yu Cheng3,4,5, Tien Yin Wong6,7,8, Ecosse Lamoureux9,10,11, Charumathi Sabanayagam12,13,14.
Abstract
This population-based cross-sectional study examined the prevalence and risk factors of suboptimal vitamin D levels (assessed using circulating 25-hydroxycholecalciferol (25(OH)D)) in a multi-ethnic sample of Asian adults. Plasma 25(OH)D concentration of 1139 Chinese, Malay and Indians (40-80 years) were stratified into normal (≥30 ng/mL), and suboptimal (including insufficiency and deficiency, <30 ng/mL) based on the 2011 Endocrine Society Clinical Practice Guidelines. Logistic regression models were used to assess the associations of demographic, lifestyle and clinical risk factors with the outcome. Of the 1139 participants, 25(OH)D concentration was suboptimal in 76.1%. In multivariable models, age ≤65 years (compared to age >65 years), Malay and Indian ethnicities (compared to Chinese ethnicity), and higher body mass index, HbA1c, education and income levels were associated with suboptimal 25(OH)D concentration (p < 0.05). In a population-based sample of Asian adults, approximately 75% had suboptimal 25(OH)D concentration. Targeted interventions and stricter reinforcements of existing guidelines for vitamin D supplementation are needed for groups at risk of vitamin D insufficiency/deficiency.Entities:
Keywords: ageing population; ethnicity; vitamin D; vitamin D deficiency; vitamin D insufficiency
Mesh:
Substances:
Year: 2017 PMID: 28327512 PMCID: PMC5372976 DOI: 10.3390/nu9030313
Source DB: PubMed Journal: Nutrients ISSN: 2072-6643 Impact factor: 5.717
Clinical and demographic characteristics of sample participants by plasma 25(OH)D concentration (n = 1139).
| Clinical and Demographic Variables | Normal (≥30 µg/L; | Suboptimal (≤29 µg/L; | |
|---|---|---|---|
| Mean (Standard Deviation) | |||
| Age (years) | 68.5 (8.2) | 66.2 (8.7) | 0.002 |
| Systolic BP (mmHg) | 144.7 (21.1) | 148.2 (22.4) | 0.02 |
| Diastolic BP (mmHg) | 77.9 (9.9) | 78.1 (10.3) | 0.7 |
| BMI (kg/m2) | 23.3 (3.7) | 25.6 (4.9) | <0.001 |
| HbA1c (%) | 6.1 (0.9) | 6.5 (1.4) | 0.001 |
| N (%) | |||
| Age ( | |||
| ≤65 | 77 (28.3) | 346 (39.9) | 0.001 |
| >65 | 195 (71.7) | 521 (60.1) | |
| Gender ( | |||
| Male | 214 (78.7) | 410 (47.3) | <0.001 |
| Female | 58 (21.3) | 457 (52.7) | |
| BMI ( | |||
| <25 | 184 (67.7) | 415 (47.9) | <0.001 |
| ≥25–29.9 | 78 (28.7) | 310 (35.8) | |
| ≥30 | 10 (3.7) | 142 (16.4) | |
| Ethnicity ( | |||
| Chinese | 137 (50.4) | 150 (17.3) | <0.001 |
| Malay | 99 (36.4) | 523 (60.3) | |
| Indian | 36 (13.2) | 194 (22.4) | |
| Smoking ( | |||
| Never | 141 (51.8) | 589 (67.9) | <0.001 |
| Current | 65 (23.9) | 119 (13.7) | |
| Ex | 66 (24.3) | 159 (18.3) | |
| Alcohol consumption ( | |||
| No | 242 (89.0) | 837 (96.5) | <0.001 |
| Yes | 30 (11.0) | 30 (3.5) | |
| Education ( | |||
| No high school education | 206 (75.7) | 657 (75.8) | 0.9 |
| High school education and above | 66 (24.3) | 210 (24.2) | |
| Income ( | |||
| <SGD 2000 | 247 (90.8) | 776 (89.5) | 0.5 |
| ≥SGD2000 | 25 (9.2) | 91 (10.5) | |
| Outdoor Job ( | |||
| No | 256 (94.1) | 832 (96.0) | 0.2 |
| Yes | 16 (5.9) | 25 (4.0) | |
| Diabetes ( | |||
| No | 221 (81.3) | 634 (73.1) | 0.007 |
| Yes | 51 (18.7) | 233 (26.9) | |
| Hypertension ( | |||
| No | 76 (27.9) | 204 (23.5) | 0.1 |
| Yes | 196 (72.1) | 663 (76.5) | |
| Hyperlipidaemia ( | |||
| No | 143 (52.6) | 446 (51.4) | 0.7 |
| Yes | 129 (47.4) | 421 (48.6) | |
* Chi-square (categorical)/independent sample t-test (continuous).
Figure 1Bar graph showing 25(OH)D status by gender and ethnicity.
Associations Of clinical and demographic variables with suboptimal 25(OH)D concentration.
| Parameters | Model 1 * | Model 2 † | ||
|---|---|---|---|---|
| OR (95% CI) | OR (95% CI) | |||
| Age (per year increase) | 0.97 (0.95, 0.99) | <0.001 | 0.98 (0.96, 1.00) | 0.055 |
| >65 | Reference | - | Reference | - |
| ≤65 | 1.66 (1.22, 2.26) | 0.001 | 1.69 (1.14, 2.52) | 0.009 |
| Gender | ||||
| Male | Reference | - | Reference | - |
| Female | 4.13 (2.99, 5.69) | <0.001 | 3.92 (2.54, 6.06) | <0.001 |
| BMI (per kg/m2 increase) | 1.10 (1.06, 1.14) | <0.001 | 1.07 (1.02, 1.11) | 0.002 |
| <25 | Reference | - | Reference | - |
| ≥25–29.9 | 1.58 (1.16, 2.17) | 0.004 | 1.31 (0.93, 1.86) | 0.1 |
| ≥30 | 4.16 (2.1, 8.21) | <0.001 | 2.82 (1.38, 5.78) | 0.005 |
| Ethnicity | ||||
| Chinese | Reference | - | Reference | - |
| Malay | 4.64 (3.33, 6.47) | <0.001 | 4.71 (3.22, 6.89) | <0.001 |
| Indian | 5.19 (3.33, 8.08) | <0.001 | 5.93 (3.61, 9.72) | <0.001 |
| Smoking | ||||
| Never | Reference | - | Reference | - |
| Current | 0.91 (0.61, 1.37) | 0.7 | 0.84 (0.53, 1.33) | 0.5 |
| Ex | 1.38 (0.93, 2.03) | 0.1 | 1.12 (0.73, 1.73) | 0.6 |
| Alcohol Consumption, yes | 0.41 (0.24, 0.71) | 0.001 | 0.38 (0.2, 0.73) | 0.004 |
| Education, ≥high school | 1.17 (0.83, 1.66) | 0.4 | 1.57 (1.05, 2.35) | 0.027 |
| Income, >$2000 | 1.37 (0.83, 2.28) | 0.2 | 2.10 (1.17, 3.76) | 0.013 |
| Outdoor Job, yes | 0.87 (0.46, 1.64) | 0.7 | 0.83 (0.41, 1.69) | 0.6 |
| Diabetes, yes | 1.65 (1.16, 2.36) | 0.006 | 0.71 (0.42, 1.21) | 0.2 |
| Hypertension, yes | 1.39 (0.99, 1.94) | 0.06 | 1.14 (0.72, 1.81) | 0.6 |
| Hyperlipidaemia, yes | 0.98 (0.74, 1.31) | 0.9 | 0.95 (0.69, 1.32) | 0.8 |
| Systolic BP, per mmHg increase | 1.01 (1.00, 1.01) | 0.027 | 1.00 (0.99, 1.01) | 0.9 |
| Diastolic BP, per mmHg increase | 1.01 (0.99, 1.02) | 0.3 | 1.00 (0.98, 1.02) | 0.8 |
| HbA1c, per % increase | 1.33 (1.15, 1.55) | <0.001 | 1.28 (1.05, 1.55) | 0.014 |
* Age and gender adjusted; † Includes all variables; ‡ Logistic regression models.
Multivariable adjusted * associations of gender with suboptimal 25(OH)D concentration stratified by ethnicity.
| Chinese | Malay | Indian | |
|---|---|---|---|
| Gender | OR (95% CI) | OR (95% CI) | OR (95% CI) |
| Male | Reference | Reference | Reference |
| Female | 4.74 (2.34, 9.60) | 9.11 (3.99, 20.7) | 0.46 (0.16, 1.36) |
* Adjusted for age, gender, BMI, smoking, alcohol consumption, education, monthly income, outdoor job, presence of diabetes, hypertension and hyperlipidaemia, systolic and diastolic blood pressure, HBA1c.
Multivariable adjusted associations of clinical, demographic and lifestyle parameters with 25(OH)D insufficiency and deficiency.
| Parameters | Insufficiency (21–29 ng/mL) | Deficiency (≤20 ng/mL) | ||
|---|---|---|---|---|
| OR (95% CI) | OR (95% CI) | |||
| Age (per year increase) | 0.99 (0.96, 1.01) | 0.4 | 0.97 (0.95, 0.99) |
|
| >65 | Reference | Reference | ||
| ≤65 | 1.34 (0.86, 2.08) | 0.2 | 2.04 (1.33, 3.14) | 0.001 |
| Gender | ||||
| Male | Reference | Reference | ||
| Female | 2.49 (1.53, 4.06) | <0.001 | 5.47 (3.40, 8.81) | <0.001 |
| BMI (per kg/m2 increase) | 1.04 (1.00, 1.09) | 0.07 | 1.09 (1.04, 1.14) | <0.001 |
| <25 | Reference | Reference | ||
| ≥25–29.9 (overweight) | 1.19 (0.81, 1.75) | 0.4 | 1.43 (0.97, 2.09) | 0.07 |
| ≥30 (obesity) | 1.76 (0.80, 3.86) | 0.2 | 3.73 (1.78, 7.84) | 0.001 |
| Ethnicity | ||||
| Chinese | Reference | Reference | ||
| Malay | 3.40 (2.22, 5.21) | <0.001 | 6.47 (4.17, 10.05) | <0.001 |
| Indian | 3.81 (2.19, 6.62) | <0.001 | 8.72 (5.04, 15.11) | <0.001 |
| Smoking | ||||
| Never | Reference | Reference | ||
| Current | 0.93 (0.56, 1.56) | 0.8 | 0.77 (0.46, 1.3) | 0.3 |
| Ex | 1.38 (0.86, 2.23) | 0.2 | 0.9 (0.55, 1.47) | 0.7 |
| Alcohol Consumption, yes | 0.30 (0.14, 0.67) | 0.003 | 0.47 (0.22, 0.99) | 0.047 |
| Education, ≥high school | 1.43 (0.91, 2.24) | 0.1 | 1.75 (1.12, 2.73) | 0.013 |
| Income, >$2000 | 2.39 (1.27, 4.5) | 0.007 | 1.83 (0.96, 3.48) | 0.065 |
| Outdoor Job, yes | 1.21 (0.57, 2.56) | 0.6 | 0.53 (0.23, 1.25) | 0.1 |
| Diabetes, yes | 0.74 (0.41, 1.33) | 0.3 | 0.7 (0.4, 1.24) | 0.2 |
| Hypertension, yes | 1.29 (0.77, 2.16) | 0.3 | 1.03 (0.62, 1.72) | 0.9 |
| Hyperlipidaemia, yes | 0.92 (0.64, 1.31) | 0.6 | 0.99 (0.7, 1.42) | 0.9 |
| Systolic BP (per mmHg increase) | 1.00 (0.99, 1.01) | 0.9 | 1.00 (0.99, 1.01) | 0.9 |
| Diastolic BP (per mmHg increase) | 0.99 (0.97, 1.02) | 0.6 | 1.00 (0.98, 1.02) | 0.9 |
| HbA1c (per % increase) | 1.21 (0.98, 1.49) | 0.08 | 1.33 (1.09, 1.64) | 0.006 |
* Multinomial logistic regression models.