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Table 4 Prevalence rate of hypertension by economic status, birth cohort and severity of the Chinese famine area

From: Infant exposure to Chinese famine increased the risk of hypertension in adulthood: results from the China Health and Retirement Longitudinal Study

Variables

Non-exposed cohorts

Fetal-exposed cohorts

Infant-exposed cohort

Preschool-exposed cohort

Low economic status

 Severely affected famine area

  Prevalence (%)

20.3

21.6

30.1

25.2

  Pa

 

0.805

0.102

0.368

  Odds ratio (95 % CI)a

Ref.

1.08(0.60–1.95)

1.69(0.90–3.18)

1.52(0.72–2.45)

  Pb

 

0.783

0.104

0.346

  Odds ratio (95 % CI)b

Ref.

1.09(0.60–1.98)

1.69(0.90–3.19)

1.35(0.73–2.49)

 Less severely affected famine area

  Prevalence (%)

17.4

16.3

26.2

24.2

  Pa

 

0.832

0.176

0.277

  Odds ratio (95 % CI)a

Ref.

0.92(0.45–1.92)

1.68(0.79–3.58)

1.52(0.72–3.21)

  Pb

 

0.678

0.19

0.300

  Odds ratio (95 % CI)b

Ref.

0.86(0.41–1.79)

1.67(0.78–3.58)

1.49(0.70–3.19)

P for interaction between area and cohorta

Ref.

0.325

0.609

0.883

P for interaction between area and cohortb

Ref.

0.341

0.635

0.956

High economic status

 Severely affected famine area

  Prevalence (%)

18.7

20.8

34.2

26.8

  Pa

 

0.654

0.013

0.119

  Odds ratio (95 % CI)a

Ref.

1.14(0.64–2.04)

2.26(1.19–4.31)

1.60(0.89–2.88)

  Pb

 

0.756

0.019

0.187

  Odds ratio (95 % CI)b

Ref.

1.10(0.61–1.97)

2.18(1.14–4.18)

1.50(0.82–2.71)

 Less severely affected famine area

  Prevalence (%)

21.4

21.7

26.5

19.8

  Pa

 

0.962

0.387

0.751

  Odds ratio (95 % CI)a

Ref.

1.01(0.58–1.76)

1.32(0.70–2.49)

0.91(0.50–1.66)

  Pb

 

0.866

0.403

0.788

  Odds ratio (95 % CI)b

Ref.

1.05(0.60–1.83)

1.31(0.69–2.48)

0.92(0.50–1.69)

P for interaction between area and cohorta

Ref.

0.845

0.291

0.198

P for interaction between area and cohortb

Ref.

0.69

0.304

0.179

  1. aEvaluating the overall risk of three exposed cohort with non-exposed as reference by single variance binary logistics regression model
  2. bEvaluating the risk of three exposed cohorts with non-exposed as reference by multi-variance binary logistics regression model after adjusted for gender, smoking and drinking