| Literature DB >> 28637448 |
Daniel Sowah1, Xiangning Fan1, Liz Dennett2, Reidar Hagtvedt3, Sebastian Straube4.
Abstract
BACKGROUND: Vitamin D deficiency is prevalent worldwide, but some groups are at greater risk. We aim to evaluate vitamin D levels in different occupations and identify groups vulnerable to vitamin D deficiency.Entities:
Keywords: 25-hydroxyvitamin D (25-(OH)D); Vitamin D level; occupation; systematic review; vitamin D deficiency
Mesh:
Substances:
Year: 2017 PMID: 28637448 PMCID: PMC5480134 DOI: 10.1186/s12889-017-4436-z
Source DB: PubMed Journal: BMC Public Health ISSN: 1471-2458 Impact factor: 3.295
Characteristics of included studies
| Group | Author (year) | Occupational Detail | Number of Subjects | Location/Latitude | Study type | 25-(OH)D | Notes | |
|---|---|---|---|---|---|---|---|---|
| Mean ± SD (nmol/L) | % Deficiency | |||||||
| Outdoor Workers | ||||||||
| Haddad and Chyu (1971) [ | Lifeguards | 8 | St. Louis, Missouri, USA (38°63′ N) | Descriptive | 160.7 ± 21.7 | |||
| Devgun (1981) [ | Gardeners | 18 | Dundee/Scotland (56°30′N) | Descriptive | 59.4 ± 19.7 | |||
| Devgun (1981) [ | Male outdoor workers | 20 | Scotland (56°30′N) | Descriptive | 62.1 ± 18.8 | |||
| Devgun (1983) [ | 1.Outdoor workers | 9 | Scotland (56°30′N) | Descriptive | 73 (1977), | Average reported as median | ||
| 2. Outdoor workers | 9 | 55 (1976), | Excluded from meta-analysis | |||||
| Azizi (2009) [ | Agriculture, physical education, construction | 122 | Beer Sheva, Israel (31°25′ N) | Case-control | 67.6 ± 21.3 | |||
| Norsang (2009) [ | 1. Farmers | 20 | Shigatse, China (29°19′ N) | Descriptive | 81.0 ± 18.0 | <75 nmol/L: 40% | ||
| 2. Farmers | 6 | Tingri, China (28°34′N) | 67.0 ± 27.0 | <75 nmol/L: 67% | ||||
| 3. Farmers | 6 | Chonggye, China (29°02′ N) | 46.0 ± 27.0 | <75 nmol/L: 83% | ||||
| Azizi (2012) [ | Israel National Water Company | |||||||
| 1. Group 1 | 34 | Israel (31°05 N) | Interventional | 74.4 ± 15.2 | ||||
| 2. Group 2 | 67 | 98.3 ± 17.2 | ||||||
| 80.4 ± 27.7 | ||||||||
| 3. Group 3 | 53 | |||||||
| Choi (2011) [ | Agriculture, Forestry, Fishery | 644 | South Korea (33° - 38°N) | Cross-sectional | 61.3 ± 18.5 | <75 nmol/L: 76.2% | ||
| Roomi (2015) [ | Outdoor workers | 15 | Lahore, Pakistan (31°55′N) | Cross-sectional | 31.4 ± 3.8 | |||
| Oh (2015) [ | 1. Craft, equipment, machine operating, and assembling workers | 2812 | South Korea (33° - 38°N) | Cross-sectional | <50 nmol/L: 61.6% | |||
| 2. Skilled agricultural, forestry, and fishery workers | 2572 | <50 nmol/L: 38.5% | ||||||
| Bacchel (2015) [ | Farmers | 6 | North-West Punjab, India (31°15′N) | Cross-sectional | <75 nmol/L: 50% | |||
| Indoor Workers | Devgun (1981) [ | Laboratory staff | 8 | Dundee, Scotland (56°30′N) | Descriptive | 43.9 ± 17.0 | ||
| Devgun (1981) [ | Indoor workers | 9 | Scotland (56°30′N) | Descriptive | 42.9 ± 15.3 | |||
| Maeda (2007) [ | Plant and office workers | 28 | Sao Paulo, Brazil (23° 34′S) | Descriptive | 94.0 ± 32.6 | |||
| Gulvady (2007) [ | Senior executives | 75 | Mumbai, India (19°08′ N) | Descriptive | <50 nmol/L: 83% | |||
| Islam (2008) [ | Garment factory workers | 200 | Dhaka, Bangledesh (23°81′N) | Descriptive | 36.7 ± 11.2 | <50 nmol/L: 86.5% | ||
| Azizi (2009) [ | Industry, civil service, etc. | 104 | Israel, Beer Sheva (31°25′ N) | Interventional | 57.5 ± 20.8 | |||
| Itoh (2011) [ | Indoor daytime workers | 4 | Kawasaki City, Japan (35°53′N) | Interrupted time series | 49.7 ± 7.9 | |||
| Vu (2011) [ | Office workers | 213 | Brisbane, Australia (27°S) | Descriptive | 62.2 ± 22.5 | <75 nmol/L: 43.3% | ||
| Choi (2011) [ | 1. Administration, clerical work | 1047 | Cross-sectional | 45.8 ± 16.5 | <75 nmol/L: 93.4% | |||
| 53.8 ± 18.5 | <75 nmol/L: 87.1% | |||||||
| 2. Engineering, assembling, and technical work | 572 | South Korea (33° - 38°N) | ||||||
| Xiang (2013) [ | Pregnant indoor workers | 311 | Guiyang, China (26°65′ N) | Descriptive | 36.7 ± 17.0 | <75 nmol/L: 12.5% | ||
| Cinar (2014) [ | Premenopausal female and male office workers. | 118 | Ankara, Turkey (39°93′N) | Prospective observational | 52.8 ± 28.4 | <75 nmol/L: 24.2% | ||
| Jeong (2014) [ | Managers, experts, specialists, etc. | 2659 | South Korea (35°91′N) | Descriptive | 40.6 ± 18.0 | <50 nmol/L: 80.4% | ||
| Sharma (2015) [ | Office working women | 50 | Udaipur, Rajasthan, India (24°59′N) | Descriptive | 46.7 ± 17.4 | |||
| Yosephin (2015) [ | Garment factory workers | 39 | Indonesia (3°35′N) | Randomized control-trial | 39.5 ± 12.0 | <75 nmol/L: 82% | ||
| Roomi (2015) [ | Indoor workers | 73 | Lahore, Pakistan (31°55′N) | Cross-sectional | 19.0 ± 1.1 | |||
| Kwon (2015) [ | Manufacturing workers | 1054 | Busan, Gyeongnam/South Korea (35°18′N) | Cross-sectional | 22.7 ± 8.1 | <50 nmol/L: 97.2% | Deficiency | |
| Insufficiency: | ||||||||
| Oh (2015) [ | 1. Clerks | 2357 | South Korea (33° - 38°N) | Cross-sectional | <50 nmol/L: 74.7% | |||
| 2. Managers, professionals and related work | 3597 | <50 nmol/L: 74.8% | ||||||
| Bacchel (2015) [ | 1. Public servants | 69 | North-West Punjab, India (31°15′N) | Cross-sectional | <75 nmol/L: 100% | |||
| 2. Professionals (businessmen) working indoors | 13 | <75 nmol/L: 100% | ||||||
| Shift Workers | Ward (2011) [ | 1. Shiftworkers with constant regular work hours | 4496 | United Kingdom (55°39′N) | Cohort | 53.0 | <50 nmol/L: 81% | Average reported as geometric mean. Excluded from meta-analysis |
| 2. Shiftworkers with varying number of hours worked per week | 6136 | 52.3 | <50 nmol/L: 79.4% | |||||
| Itoh (2011) [ | 1. Rotating shift workers without night shift | 4 | Osaka Prefecture, Japan (34.5°N) | Cross-sectional | 63.1 ± 6.3 | |||
| 2. Rotating shift workers with night shift | 4 | 64.4 ± 8.1 | ||||||
| Kim (2013) [ | Shift workers without day shift | 627 | South Korea (35°91′N) | Descriptive | 40.0 ± 14.7 | |||
| Jeong (2014) [ | Shiftworkers | 969 | South Korea (35°91′N) | Descriptive | 40.0 ± 17.7 | <50 nmol/L: 80.1% | ||
| Kwon (2015) [ | Manufacturing workers | 872 | Busan, Gyeongnam/South Korea (35°18′N) | Cross-sectional | 22.2 ± 8.1 | <25 nmol/L: 71% | ||
| Romano (2015) [ | Shiftworkers | 96 | Northern Italy, Milan Province, Lomabardy (45° 30′N) | Cross-sectional | 33.4 ± 13.2 | <75 nmol/L: 24% | ||
| Lead/Smelter | Greenberg (1986) [ | Lead and cadmium exposed workers | 37 | Pittsburgh & Cleveland, United States (40°44′N & 41°50′N) | Descriptive | 62.5 ± 24.5 | 5.4% | Mean 1α, 25-(OH)2D: 122.7 ± 36.5 pmol/L. Vitamin D deficiency was not defined. |
| Mason (1990) [ | Lead exposed workers | 63 | United Kingdom (55°39′N) | Cohort | Mean 1α, 25-(OH)2D: 90.5 ± 29.5 pmol/L | |||
| Chalkley (1998) [ | Smelter workers | 19 | England (52°36′N) | Descriptive | Mean: 71.4 Median: 71.0 | 1α, 25-(OH)2D3 Mean: 77.3 pmol/L; Median: 84.0 pmol/L. | ||
| Kristal-Boneh (1998) [ | 1. Lead-exposed factory workers (battery and recycling) | 56 | Israel (31°25′ N) | Cross-sectional | 86.0 ± 25.2 | Mean 1α, 25-(OH)2D: 198 ± 64.8 pmol/L | ||
| 2. Non-lead exposed workers | 90 | 79.0 ± 20.5 | Mean 1α, 25-(OH)2D: 165 ± 42.3 pmol/L | |||||
| Potula (2005) [ | Smelter workers | 73 | Bunker Hill, Idaho, USA (43°91′N) | Descriptive | Mean 1α, 25-(OH)2D: 115.9 ± 38.0 pmol/L | |||
| Coal-miners | Shuster (1981) [ | 1. Underground miners | 101 | Newcastle Upon Tyne (54°98′N) | Cross-sectional | 73.8 ± 73.4 | ||
| 2. Surface workers | 19 | 82.3 ± 67.6 | ||||||
| 3. Miners not at work | 6 | 83.5 ± 67.4 | ||||||
| Shuster (1982) [ | 1. Underground miners | 60 | United Kingdom (55°39′N) | Cross-sectional | 58.5 ± 24.3 | |||
| 2. Surface workers | 28 | 62.6 ± 21.7 | ||||||
| Sarikaya (2006) [ | 1. Underground miners | 50 | Zonguldak, Turkey (41°45′N) | Cross-sectional | 24.5 ± 28.2 | |||
| 2. Surface workers | 50 | 35.3 ± 29.3 | ||||||
| Healthcare Students | Maeda (2007) [ | Medical students | 44 | Sao Paulo (23° 34′S), Brazil | Descriptive | 81.5 ± 35.8 | ||
| Gonzalez-Padilla (2011) [ | Medical students | 103 | Gran Canaria, Canary Islands (27°92′N) | Descriptive | 69.6 ± 31.0 | <75 nmol/L: 28.6% | Paper reported unit as ng/dL but ng/ml was used for calculation | |
| Kaehler (2012) [ | Female healthcare professional students | 215 | Innsbruck, Austria (47°27′N) | Cross-sectional | 50.3 ± 16.6 | <75 nmol/L: 33.5% | ||
| Al-Elq (2012) [ | Medical students | 198 | Dammam, Saudi Arabia (26°39′N) | Cross-sectional | 21.2 ± 11.9 | <75 nmol/L: 4% | ||
| Manickam (2012) [ | Medical students and residents | 104 | Chicago, IL, USA (42°N) | Descriptive | 54.0 ± 28.0 | <75 nmol/L: 77% | ||
| Zabihiyeganeh (2014) [ | Medical students | 100 | Tehran, Iran (35° 69′N) | Cross-sectional | 42.0 ± 11.7 | <75 nmol/L: 15% | ||
| Milovanovic (2015) [ | Medical, pharmacy and dental students | 86 | Kragujevac, Serbia (44°N) | Descriptive | 33.1 ± 12.1 | <50 nmol/L: 88.4% | ||
| Medical Residents | Haney (2004) [ | Medical residents | 34 | Portland, OR, USA (45°52′ N) | Interrupted series | 56.4 ± 20.1 | <50 nmol/L: 38% | Paper reported unit as ng/dL but ng/ml was used for calculation |
| Maeda (2007) [ | Medical residents | 49 | Sao Paulo, Brazil (23° 34′S) | Descriptive | 67.1 ± 27.0 | |||
| Orlandin Premaor (2014) [ | Medical residents | 73 | Porto Alegre, Brazil (30°S) | Cross-sectional | 44.7 ± 20.0 | <50 nmol/L: 57.4% | ||
| Multani (2010) [ | Medical residents | 214 | Mumbai, India (19°08′ N) | Cross-sectional | 31.1 ± 18.6 | <50 nmol/L: 87.2% | ||
| Singh (2011) [ | Medical residents | 80 | Varanasi, India (25°N) | Cross-sectional | 22.8 ± 18.2 | <75 nmol/L: 11% | ||
| Growdon (2012) [ | Trainee doctors (Residents) | 102 | Boston, MA, USA (42°36′ N) | Descriptive | 67.0 ± 26.0 | <75 nmol/L: 44% | ||
| Mendoza (2013) [ | Medical residents | 20 | Mexico City, Mexico (19°43′N) | Cross-sectional | 42.4 ± 13.0 | <50 nmol/L: 75% | ||
| Ramirez-Vick (2015) [ | Medical residents | 51 | San Juan, Puerto Rico (18°47′ N) | Descriptive | 54.3 ± 19.4 | <75 nmol/L: 45% | ||
| Practising Physicians | Gann (1996) [ | Male physicians | 414 | United States (37°09′N) | Case-control | Median: 71.1 | <50 nmol/L: 6.5% | |
| Goswami (2000) [ | Physicians and nurses | 19 | Delhi, India (28°61′N) | Descriptive | 13.0 ± 7.9 | Mean 1α, 25-(OH)2D: 93.6 ± 29.0 pmol/L | ||
| Kramm (2010) [ | Physicians | 28 | Madison, Wisconsin (43°07′N) | Descriptive | 80.0 ± 25.0 | <50 nmol/L: 21% | 25-(OH)D deficiency was defined as <62.5 nmol/L | |
| Mahdy (2010) [ | Physicians and nurses | 340 | Doha, Qatar (25°29′N) | Observational | 29.3 | <75 nmol/L: 9.5% | SD was not provided. Excluded from meta-analysis | |
| Lee (2011) [ | Male physicians | 389 | United States (37°09′N) | Case-control | 64.0 | Only control values were used for analysis | ||
| Haliloglu (2016) [ | Medical doctors | Unknown | Istanbul/Turkey (41°N) | Prospective observational | Winter: 42.8 ± 22.5 Summer: 58.1 ± 24.3 | Total number of healthcare workers were 190. Actual number of medical doctors was not provided | ||
| Munter (2015) [ | Hospital- and community-based physicians | 81 | Jerusalem (31.4°N), Israel | Descriptive | 56.2 ± 16.3 | <75 nmol/L: 24.6% | ||
| Nurses | Platz (2000) [ | Nurses | 326 | United States (37°09′N) | Case-control | 67.0 ± 25.5 | Mean 1α, 25-(OH)2D: Controls: 77.3 ± 20.6 pmol/L | |
| Eliassen (2011) [ | Nurses | 1218 | United States (37°09′ N) | Case-control | 62.4 ± 24.0 | Only control values used | ||
| Hattapornsawan (2012) [ | Nurses | 217 | Nonthaburi, Thailand (13°86′N) | Cross-sectional | <75 nmol/L: 45.6% | |||
| Wallingford (2014) [ | Premenopausal nurses | 83 | Kingston, ON, Canada (44°23′N) | Cross-sectional | 83.5 ± 36.2 | <50 nmol/L: 11.2% | ||
| Wang (2014) [ | Nurses | 584 | United States (37°09′N) | Case-control | 61.1 ± 22.8 | Only control values used | ||
| Haliloglu (2016) [ | Nurses | Unknown | Istanbul/Turkey (41°N) | Prospective observational | 41.8 ± 16.8 | Authors did not report number of subjects | ||
| Bertrand (2016) [ | Nurses | 835 | Boston/USA (42°36′N) | Case-control | 68.0 ± 25.8 | Only control values used | ||
| Madani (2015) [ | Nurses | 200 | Kashan/Iran (33°98′N) | Cross-sectional | 42.4 ± 52.8 | <75 nmol/L: 178 (89%) | 25-(OH)D 25–75 nmol/L (deficiency); | |
| 25-(OH)D ≤ 25 nmol/L (severe deficiency) | ||||||||
| Other Healthcare Employees | Platz (2000) [ | Health professionals | 150 | United States (37°09′N) | Cohort | 45.5 ± 15.0 | Mean 1α, 25-(OH)2D: 79.6 ± 15.7 pmol/L | |
| Nakamura (2001) [ | Nursing home employees | 77 | Niigata, Japan (37° 48′ to 59′N) | Cross-sectional | 42.1 ± 15.1 | <50 nmol/L: 26% | Mean 1α, 25-(OH)2D: 111.1 ± 33.6 pmol/L | |
| Platz (2004) [ | Health professionals | 460 | United States (37°09′N) | Case-control | 59.7 ± 20.5 | Mean 1α, 25-(OH)2D: 83.8 ± 17.0 pmol/L. | ||
| Arya (2004) [ | Hospital staff | 92 | Lucknow, 26.55°N, 80.59°E | Descriptive | 30.7 ± 27.2 | <50 nmol/L: 78.3% | Mean 1α, 25-(OH)2D: 97.4 ± 48.2 pmol/L | |
| Hanwell (2010) [ | 1. Hospital workers (in winter) | 47 | South Italy (latitude 40°N) | Descriptive | 38.8 ± 29.0 | <75 nmol/L: 87% | ||
| 2. Hospital workers (in summer) | 23 | 58.6 ± 16.5 | <75 nmol/L: 78% | |||||
| Beloyartseva [ | Healthcare professionals | 2119 | India, various cities (20°59′N) | Descriptive | 35.8 ± 26.5 | <75 nmol/L: 15% | ||
| Plotnikoff (2012) [ | Health care system employees | 10,646 | Minnesota, United States (46°73′ N) | Prospective observational | 70.1 ± 34.0 | <75 nmol/L: 31.9% | ||
| Porojnicu[ | Hospital employees | 105 | Bucharest, Romania (45° N) | Descriptive | <80 nmol/L: 17% | |||
| Gannage-Yared (2014) [ | Hospital employees | 392 | Beirut, Lebanon (33°89′N) | Descriptive | 39.0 ± 19.7 | < 75 nmol/L: 23.5% | ||
| Skarphedinsdottir (2014) [ | 1. Anaesthesia health care staff | 106 | Reykjavik, Iceland (64°08′N) | Descriptive | 70.5 ± 30.9 | <75 nmol/L: 56.6% | ||
| 2. Anaesthesia health care staff | 124 | 70.0 ± 30.0 | <75 nmol/L: 61.3% | |||||
Occupations were categorized as indoor workers, outdoor workers, shiftworkers, coalminers, lead/smelter workers, medical residents, healthcare students, practising physicians, nurses and other healthcare professionals. Data on 25-(OH)D level and vitamin D deficiency as well as location (latitude) of study were extracted. Where necessary, additional notes and explanations are included
Abbreviations: 25-(OH)D = 25-hydroxyvitamin D; 1α, 25-(OH)2D = 1,25-dihydroxyvitamin D
Assay type, measure of coefficient of variation (reliability) and seasons of included studies
| Category | Study ID | Assay type | Reliability | Season of year | Study quality |
|---|---|---|---|---|---|
| Outdoor Workers | Haddad and Chyu [ | Competitive protein binding assay | CV: 8–14% | Spring, Summer | High |
| Devgun [ | Competitive protein binding assay | Inter-assay CV: 10% | All year | High | |
| Devgun [ | Competitive protein binding assay | Inter-assay CV: 10.7% | All year | High | |
| Devgun [ | Competitive protein binding assay | Inter-assay CV: 10.6% | Autumn, Winter | High | |
| Azizi [ | Competitive protein binding assay | Unknown | All year | Medium | |
| Norsang [ | RIA | Unknown | Autumn | Medium | |
| Azizi [ | RIA | Unknown | Winter | Medium | |
| Choi [ | RIA | Inter-assay CV: 11.7–12.5% | All year | High | |
| Roomi [ | EIA | Inter-assay CV: 4.9% | All year | High | |
| Oh [ | RIA | Unknown | Unknown | Low | |
| Bacchelv [ | Unknown | Unknown | Unknown | Low | |
| Indoor Workers | Devgun [ | Competitive protein binding assay | Inter-assay CV: 10% | All year | High |
| Devgun [ | Competitive protein binding assay | Inter-assay CV: 10.7% | All year | High | |
| Maeda [ | Immunoradiometric assay | Inter-assay CV: 16% (for lowest values; 3% for highest values) | Summer, Spring, Winter | High | |
| Gulvady [ | RIA | Unknown | Unknown | Low | |
| Islam [ | EIA | Inter-assay CV: 7% Intra-assay CV: 5.4% | Unknown | Medium | |
| Azizi [ | Competitive protein binding assay | Unknown | All year | Medium | |
| Itoh [ | RIA/EIA | Inter –assay CV: 21.9 | Winter, Autumn | High | |
| Vu [ | Chemiluminescent assay | Inter-assay CV: 6–9% | Summer, Winter | High | |
| Choi [ | RIA | Inter-assay CV: 11.7–12.5% | All year | High | |
| Xiang [ | HPLC-MS/MS tandem | Inter-assay CV: 6.9–9.5% | All year | High | |
| Cinar [ | HPLC | Inter-assay CV: 3.4% | Summer, | High | |
| Jeong [ | Unknown | Unknown | Unknown | Low | |
| Sharma [ | Chemiluminescent assay | Unknown | Unknown | Low | |
| Yosephin [ | EIA | Unknown | Unknown | Low | |
| Roomi [ | EIA | Inter-assay CV: 4.9% | All year | High | |
| Kwon [ | EIA | Unknown | Winter, Spring | Medium | |
| Oh [ | RIA | Unknown | Unknown | Low | |
| Bacchel [ | Unknown | Unknown | Unknown | Low | |
| Shiftworkers | Ward [ | ELISA | Intra-assay CV: 5.5–7.2% (concentrations standardized according to mean of values from vitamin D External Quality Assurance Survey) | Unknown | Medium |
| Itoh [ | RIA | Intra- and inter-day variation: 4.3–7% | Summer | High | |
| Kim [ | RIA | Unknown | All year | Medium | |
| Jeong [ | Unknown | Unknown | Unknown | Low | |
| Kwon [ | EIA | Unknown | Winter, Spring | Medium | |
| Romano [ | Chemiluminescent assay | Unknown | Spring | Medium | |
| Lead/Smelter | Greenberg [ | Competitive protein binding assay | Unknown | Unknown | Low |
| Mason [ | Radioreceptor assay | Inter-assay CV: 11.5% | Unknown | Medium | |
| Chalkley [ | RIA | Unknown | Unknown | Low | |
| Kristal-Boneh [ | Competitive protein binding assay | Inter-assay CV: 15.2% | Summer | High | |
| Potula [ | RIA | Unknown | Unknown | Low | |
| Coalminers | Shuster [ | Competitive protein binding assay | Unknown | Spring, Summer | Medium |
| Shuster [ | Competitive protein binding assay | Unknown | Winter, Autumn | Medium | |
| Sarikaya [ | ELISA | Unknown | Unknown | Low | |
| Healthcare Students | Maeda [ | Immunoradiometric assay | Inter-assay CV: 16% (for lowest values; 3% for highest values) | Summer, Spring, Winter | High |
| Gonzalez-Padilla [ | Immunochemiluminescence | Inter-assay CV: 7.1–10% | Unknown | Medium | |
| Kaehler [ | Electro-chemoluminescence | Unknown | Spring | Medium | |
| Al-Elq [ | Chemiluminescent assay | Unknown | Winter | Medium | |
| Manickam [ | Chemiluminescent assay | Inter-assay CV: 13.9% | Unknown | Medium | |
| Zabihiyeganeh [ | RIA | Inter-assay CV: 6.4% | Autumn | High | |
| Milovanovic [ | Unknown | Unknown | Spring, Summer | Low | |
| Medical Residents | Haney [ | RIA | Unknown | Autumn, Spring | Medium |
| Maeda [ | Immunoradiometric assay | Inter-assay CV: 16% (for lowest values; 3% for highest values) | Summer, Spring, Winter | High | |
| Premaor [ | Chemiluminescent assay | Intra-assay CV: 6% | Autumn | High | |
| Multani [ | RIA | Inter-assay CV: 6.49% | Spring, Summer | High | |
| Singh [ | RIA | Unknown | Winter, Summer | Medium | |
| Growdon [ | RIA | Inter-assay CV: 6.2–12.5% | Winter | High | |
| Mendoza [ | Chemiluminescent assay | Inter-assay CV: 2.1% | Summer | High | |
| Ramirez-Vick [ | LC-MS/MS | Unknown | Spring, Winter | Medium | |
| Practising Physicians | Gann [ | RIA | Intra-assay CV: 8.1% | Unknown | Medium |
| Goswami [ | RIA | Inter-assay CV: 13% | Winter, Summer | High | |
| Kramm [ | HPLC | Unknown | Unknown | Low | |
| Mahdy [ | Unknown | Unknown | Unknown | Low | |
| Lee [ | RIA | Intra-assay CV: 13.8% | Summer, Autumn | high | |
| Haliloglu [ | HPLC | Inter-assay CV: 3.1–4.7% | Winter, Summer | High | |
| Munter [ | Chemiluminescent assay | Unknown | Unknown | Low | |
| Nurses | Platz [ | RIA | Intra-assay CV: 7.5% | Unknown | Medium |
| Eliassen [ | RIA | Overall CV: 10.7% and 6% | Unknown | Medium | |
| Hattapornsawan [ | LC-MS/MS | Inter-assay CV: 6.3% | Unknown | Medium | |
| Wallingford [ | RIA | Intra-assay CV: 0.99% | All year | High | |
| Wang [ | RIA | Overall CV: 10.7% and 6% | Unknown | Medium | |
| Haliloglu [ | HPLC | Inter-assay CV: 3.1–4.7% | Winter, Summer | High | |
| Bertrand [ | High affinity protein-binding assay or RIA | Overall CV: 17.6% and 6% | Unknown | Medium | |
| Madani [ | ELISA | Unknown | Summer | Medium | |
| Other Healthcare Professionals | Platz [ | RIA | Intra-assay CV: 6.7% | Unknown | Medium |
| Nakamura [ | HPLC | Inter-assay CV: 2.6–4.2% | Winter | High | |
| Platz [ | RIA | Intra-assay CV: 5.4–5.6% | All year | High | |
| Arya [ | RIA | Inter-assay CV: 8.4% | Unknown | Medium | |
| Hanwell [ | RIA | Inter-assay CV: 12% | Winter, Summer | High | |
| Beloyartseva [ | RIA | Unknown | Winter | Medium | |
| Plotnikoff [ | Chemiluminescent assay | CV: 9.8–12.5% | Winter, Spring | High | |
| Porojnicu [ | HPLC | Inter-assay CV: 12% | Winter | High | |
| Gannage-Yared [ | Chemiluminescent assay | Inter- and Intra CV: <12% | All year | High | |
| Skarphedinsdottir [ | HPLC | Unknown | Spring | Medium | |
| Haliloglu [ | HPLC | Inter-assay CV: 3.1–4.7% | Winter, Summer | High |
The assay type, coefficient of variation and the season of each study were extracted to assess the methodological quality of each study
Abbreviations: CV coefficient of variation, RIA radioimmunoassay, LC-MS/MS liquid chromatography-mass spectrometry/mass spectrometry, ELISA enzyme-linked immunosorbent assay, EIA electrochemiluminescence immunoassay, HPLC high performance liquid chromatography
Fig. 125-hydroxyvitamin D (25-(OH)D) levels in different occupational groups. Data represent the weighted means pooled from the means of the included studies obtained for each occupational category. Error bars represent pooled standard error of means computed as , where Sp is pooled variance, n1 represents sample size of group 1, and n2 represents sample size of group 2
Fig. 2Percent vitamin D status in different occupational groups. Vitamin D deficiency (white bars) was defined according to the Endocrine Society’s (ES) categorization as a serum level of 25-(OH)D ≤ 50 nmol/L (20 ng/ml). Each white bar graph represents % of subjects of each group with a serum 25-(OH)D ≤ 50 nmol/L. The black bars represent percent vitamin D deficiency or insufficiency in different occupational groups. Vitamin D insufficiency was defined based on the ES’s criteria, which indicates a serum level of 25-(OH)D ≤ 75 nmol/L (30 ng/ml) as insufficient. Each black bar graph represents the % of subjects of each group with a serum 25-(OH)D level ≤ 75 nmol/L. The numbers within the bars, N, represent the total number of subjects contributing to each category for whom vitamin D deficiency, insufficiency, or sufficiency could be determined
Occupational groups, % deficiency, and relative risk
| Occupational group | Number of subjects | Number of vitamin D deficient subjects | % deficiency | Relative risk |
|---|---|---|---|---|
| All groups (total) | 46,426 | 29,255 | 63.0 | 1.00 (baseline) |
| Indoor workers | 12,204 | 9462 | 77.5 | 1.23 (95% CI: 1.22 to 1.24) |
| Outdoor workers | 6060 | 2923 | 48.2 | 0.77 (95% CI: 0.75 to 0.79) |
| Shiftworkers | 11,697 | 9354 | 80 | 1.27 (95% CI: 1.26 to 1.28) |
| Medical residents | 574 | 375 | 65.3 | 1.04 (95% CI: 0.97 to 1.10) |
| Healthcare students | 702 | 504 | 71.6 | 1.14 (95% CI: 1.09 to 1.19) |
| Practising physicians | 838 | 386 | 46.1 | 0.73 (95% CI: 0.68 to 0.78) |
| Nurses | 500 | 213 | 42.3 | 068 (95% CI: 0.61 to 0.75) |
| Other healthcare workers | 13,851 | 6038 | 43.6 | 0.69 (95% CI: 0.68 to 0.71) |
Vitamin D deficiency was defined as 25-(OH)D < 50 nmol/L
Abbreviation: CI confidence interval
Occupational groups, combined % insufficiency and deficiency, and relative risk
| Occupational group | Number of subjects | Number of vitamin D insufficient subjects | % insufficiency | Relative risk |
|---|---|---|---|---|
| All groups (total) | 18,704 | 13,735 | 73.4 | 1.00 (baseline) |
| Indoor workers | 2383 | 2165 | 90.9 | 1.24 (95% CI: 1.22 to 1.25) |
| Outdoor workers | 682 | 513 | 75.2 | 1.02 (95% CI: 0.98 to 1.07) |
| Shiftworkers | 96 | 91 | 90.8 | 1.24 (95% CI: 1.16 to 1.32) |
| Medical residents | 233 | 205 | 88.2 | 1.20 (95% CI: 1.15 to 1.26) |
| Healthcare students | 720 | 632 | 87.8 | 1.20 (95% CI: 1.16 to 1.23) |
| Practising physicians | 421 | 403 | 95.7 | 1.30 (95% CI: 1.28 to 1.33) |
| Nurses | 417 | 385 | 92.3 | 1.26 (95% CI: 1.22 to 1.29) |
| Other healthcare workers | 13,752 | 9341 | 67.9 | 0.93 (95% CI: 0.91 to 0.94) |
Vitamin D insufficiency was defined as 25-(OH)D < 75 nmol/L
Abbreviation: CI confidence interval
Fig. 3Effect of seasons on 25-(OH)D level in indoor (white bars) and outdoor (black bars) workers. Data represent mean ± standard error of the mean of each season for the given occupational group