Chart 1
Predicted daily minutes in unpaid housework, by telework status and gender, 2022

Non-teleworkers¹ On-site teleworkers¹,² WFH teleworkers¹,²,³ 0 50 100 150 minutes AllAll Men+ ⁴Men+ ⁴ Women+ ⁴Women+ ⁴
1.
Significantly different (p<0.05) from the reference category (men), for women, within telework status.
2.
Significantly different (p<0.05) from the reference category (non-teleworkers) for men.
3.
Significantly different (p<0.05) from the reference category (non-teleworkers) for women.
4.
Given that the non-binary population is small, data aggregation to a two-category gender variable is sometimes necessary to protect the confidentiality of responses. In these cases, individuals in the category "non-binary persons" are distributed into the other two gender categories and are denoted by the "+" symbol.
Note(s):
WFH = work-from-home. The daily minutes presented above are predicted using ordinary-least-squares linear regression models, estimated separately by gender, and adjusting for socioeconomic characteristics. See the full study for more information on the methodology.
Source(s):
Time Use Survey, 2022 (4503).

Chart description


This is a bar clustered chart.

Predicted daily minutes in unpaid housework, by telework status and gender, 2022, minutes
  All Men+ ⁴ Women+ ⁴
Non-teleworkers¹ 66.1 48.5 87.3
On-site teleworkers¹,² 76.5 66.8 88.0
WFH teleworkers¹,²,³ 82.4 62.5 102.9
1.
Significantly different (p<0.05) from the reference category (men), for women, within telework status.
2.
Significantly different (p<0.05) from the reference category (non-teleworkers) for men.
3.
Significantly different (p<0.05) from the reference category (non-teleworkers) for women.
4.
Given that the non-binary population is small, data aggregation to a two-category gender variable is sometimes necessary to protect the confidentiality of responses. In these cases, individuals in the category "non-binary persons" are distributed into the other two gender categories and are denoted by the "+" symbol.
Note(s):
WFH = work-from-home. The daily minutes presented above are predicted using ordinary-least-squares linear regression models, estimated separately by gender, and adjusting for socioeconomic characteristics. See the full study for more information on the methodology.
Source(s):
Time Use Survey, 2022 (4503).
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