Table 2 Associations of various lifestyle factors with vitamin D inadequacy among the elderly Chinese population

Men

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Women

1.544 (1.388–1.717)

<0.0001

60–69

ref

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70–79

1.066 (0.948–1.199)

0.9405

1.126 (0.952–1.332)

0.6001

1.01 (0.858–1.19)

0.5367

80+

1.149 (0.923–1.432)

0.3334

1.132 (0.816–1.572)

0.6947

1.159 (0.86–1.56)

0.3447

18.5–24.0

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<18.5

1.238 (1.049–1.462)

0.0259

1.261 (0.994–1.6)

0.0857

1.225 (0.971–1.546)

0.1284

24.0–28.0

1.005 (0.885–1.141)

0.1451

0.974 (0.806–1.177)

0.1329

1.031 (0.868–1.226)

0.5529

>28.0

1.079 (0.904–1.289)

0.9713

1.11 (0.86–1.433)

0.7736

1.044 (0.815–1.336)

0.7716

Summer

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Spring

2.487 (1.849–3.346)

<0.0001

2.137 (1.398–3.268)

0.0015

2.858 (1.887–4.327)

0.0005

Autumn

1.462 (1.235–1.731)

0.2201

1.269 (0.996–1.618)

0.3442

1.66 (1.313–2.098)

0.4294

Winter

1.591 (1.301–1.947)

0.6809

1.245 (0.929–1.667)

0.3491

1.977 (1.496–2.614)

0.1581

High

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Low

2.233 (1.952–2.553)

<0.0001

2.119 (1.743–2.575)

<0.0001

2.352 (1.954–2.832)

<0.0001

Medium

1.646 (1.442–1.877)

0.0939

1.665 (1.37–2.025)

0.1111

1.625 (1.358–1.944)

0.4636

Illiteracy

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Literate

0.854 (0.704–1.036)

0.1085

0.875 (0.661–1.158)

0.3515

0.837 (0.641–1.094)

0.1928

General rural areas

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Large cities

1.287 (1.109–1.494)

0.0026

1.466 (1.179–1.823)

0.0022

1.147 (0.935–1.408)

0.2101

Small to medium cities

1.136 (0.987–1.307)

0.664

1.093 (0.887–1.346)

0.2145

1.18 (0.974–1.429)

0.0716

Poor rural areas

1.052 (0.894–1.238)

0.2912

1.234 (0.974–1.565)

0.6048

0.916 (0.732–1.145)

0.0573

No

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Yes

1.012 (0.894–1.145)

0.8529

0.911 (0.76–1.093)

0.3181

1.099 (0.928–1.301)

0.2751