Expected average number of children by assessment
The number of children people plan to have based on housing quality is categorized by level of satisfaction with living conditions. Rows represent different assessment categories, from very good to average housing conditions. The data is presented as a cross-section with columns divided by respondent gender, allowing for a comparison between women's and men's expectations. The figures demonstrate how housing assessment correlates with the expected number of children: for those who rate their housing as very good, the average expected number of children is 1.875575 for women and 1.895106 for men
Chart of the average expected number of children by housing condition assessment for women and men
Set in numbers
This is a cross-section: 6 series across 2 breakdowns. 12 values in total.
The largest value belongs to “row 1” — 2; the smallest is “50-60 – Среднее” at 1.8.
All table numbers are series: 6
| Series | Женщины | Мужчины |
|---|---|---|
| строка 1 | 2,00 | 2,00 |
| 90-100 – Очень хорошее | 1,88 | 1,90 |
| 70-80 – Хорошее | 1,86 | 1,86 |
| 50-60 – Среднее | 1,82 | 1,81 |
| 30-40 – Плохое | 1,85 | 1,82 |
| 0-20 – Очень плохое | 1,70 | 1,84 |
How to read this table
The table rows group individuals by quality of living: from very good (90-100 points) to average (50-60 points). Comparing values across rows helps illustrate how home comfort levels influence reproductive plans. The columns highlight the gender gap in expectations, as data is segmented by women and men. This enables analysis of the relationship between material well-being and the population's demographic attitudes
The same indicator in other breakdowns (1)
More in the section Results of the survey»
Period and application
The indicators were obtained through Rosstat's final observation and represent a one-time data cross-section without reference to a specific year. The information is structured by gender and qualitative assessment of the housing stock. This data is useful for demographers, sociologists, and housing policy specialists studying the link between living conditions and fertility rates
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