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Table 2 Logistic regression and subgroup analysis for association of anemia with VB12 status under different DDS

From: Vitamin B12 is associated negatively with anemia in older Chinese adults with a low dietary diversity level: evidence from the Healthy Ageing and Biomarkers Cohort Study (HABCS)

Variables

Unadjusted

Basic modela

Final Modelb

OR(95%CI)

P

OR(95%CI)

P

OR (95%CI)

P

All (N = 2405)

0.61 (0.51–0.73)

<0.001

0.69 (0.57–0.83)

<0.001

0.70 (0.57–0.85)

<0.001

Low DDS group (N = 1252)

0.55 (0.43–0.70)

<0.001

0.59 (0.46–0.76)

<0.001

0.59 (0.45–0.77)

<0.001

DDS≤3(N = 799)

0.55 (0.41–0.75)

<0.001

0.6 (0.44–0.82)

0.002

0.62 (0.44–0.88)

0.007

DDS=4 (N = 453)

0.55 (0.36–0.83)

0.005

0.61 (0.40–0.94)

0.024

0.47 (0.29–0.77)

0.003

High DDS group (N = 1127)

0.72 (0.55–0.94)

0.015

0.85 (0.64–1.12)

0.245

0.88 (0.65–1.19)

0.411

DDS=5 (N = 475)

0.99 (0.67–1.40)

0.973

1.13 (0.74–1.72)

0.564

1.15 (0.73–1.83)

0.548

DDS≥6 (N = 652)

0.57 (0.39–0.81)

0.002

0.67 (0.45–0.99)

0.042

0.7 (0.45–1.08)

0.104

Gender

      

The male low DDS group (N = 579)

0.58 (0.41–0.84)

0.003

0.64 (0.44–0.94)

0.021

0.62 (0.42–0.93)

0.027

The female low DDS group (N = 673)

0.52 (0.38–0.73)

<0.001

0.57 (0.40–0.80)

0.001

0.59 (0.41–0.85)

0.005

The male high DDS group (N = 559 )

0.74 (0.50–1.12)

0.152

0.90 (0.59–1.39)

0.644

0.98 (0.61–1.56)

0.945

The female High DDS group (N = 568 )

0.67 (0.47–0.96)

0.030

0.79 (0.54–1.15)

0.217

0.82 (0.55–1.23)

0.340

Low DDS group with age ≥ 80 (N = 830)

0.63 (0.48–0.84)

0.002

0.66 (0.50–0.89)

0.005

0.66 (0.48–0.90)

0.010

Low DDS group with age < 80 (N = 442)

0.42 (0.25–0.69)

0.001

0.43 (0.26–0.70)

0.001

0.43 (0.25–0.72)

0.002

High DDS group with age ≥ 80 (N = 652)

0.93 (0.67–1.28)

0.639

0.97 (0.7–1.35)

0.869

1.00 (0.70–1.42)

0.982

High DDS group with age < 80 (N = 475)

0.57 (0.33–0.98)

0.043

0.58 (0.33–1.00)

0.050

0.63 (1.13–2.93)

0.109

  1. aBasic model,adjusted for age,gender
  2. bFinal model, adjusted for age, gender, race, education levels, current marital status, physic activity habits, smoking habits, tea drinking habits, BMI