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Table 4 Multiple regression analysis predicting attitudes toward lockdown and adverse lifestyle

From: Influence on attitudes and lifestyle due to lockdown amidst COVID-19 pandemic: a perception-based analysis among Bangladeshi residents

Characteristics

Attitudesa

Adverse lifestyleb

B

SE

β

B

SE

β

Gender

 Male

−1.06

0.47

−0.06*

1.52

0.27

0.15***

 Female

  

c

  

c

Age

 Young (18–25 years)

   

0.70

0.43

0.07

 Older (> 25 years)

     

c

Marital status

 Unmarried

−5.83

2.30

−0.34*

1.70

1.30

0.17

 Married

−4.11

2.27

−0.24

1.44

1.30

0.15

 Divorced

  

c

  

c

Education

 No formal education

−0.59

1.86

−0.01

2.08

1.05

0.08*

 Primary

−4.57

1.80

−0.11*

1.11

1.02

0.05

 Secondary

−5.10

1.60

−0.19**

0.82

0.91

0.05

 Higher secondary

−3.85

1.55

−0.22*

−0.03

0.89

−0.00

 University

−3.37

1.54

−0.15*

−0.55

0.87

− 0.04

 Higher education

  

c

  

c

Occupation

 Housewife

−0.49

1.08

− 0.02

− 0.16

0.63

− 0.01

 Service holder

− 0.70

0.98

− 0.03

− 0.11

0.59

− 0.01

 Business

−4.12

1.06

−0.14***

− 0.97

0.63

− 0.06

 Unemployed/ other

−1.84

1.02

−0.06

0.22

0.60

0.01

 Student

  

c

  

c

Residence

 Rural

−0.63

0.45

−0.04

0.98

0.26

0.10***

 Urban

  

c

  

c

  1. B Unstandardized regression coefficient, SE Standard error, β Standardized regression coefficient
  2. *p < .05,**p < .01, ***p < .001
  3. aModel summery (Attitudes): Covariates: Gender, Marital status, Education, Occupation and Residence; F(13, 1621) = 5.47, p < .001, R2Adj = .034
  4. bModel summery (Adverse lifestyle): Covariates: Gender, Age, Marital status, Education, Occupation and Residence; F(14, 1620) = 7.76, p < .001, R2Adj = .055
  5. cReference category
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