3.1 Descriptive analysis
Table 1 reports the results of the descriptive statistical analysis of urban and rural samples. 25.80% of elder people in the full sample are in disability and the disability rate of urban elderly women is higher than that of rural elderly women. The mean number of births in the sample is around four, with rural women having more births than urban women, the age at first birth is about 23 and the age is slightly higher for urban women than for rural women, the age at last birth is about 34 and the average age at last birth is higher for rural women, the average childbearing period is around 11.43 years and rural women have a slightly longer period, the average birth interval is 2.59 years. For control variables, the average age of the selected samples is 84.57 years old, and the Han nationality accounted for 94.36% and 57.73% of the elderly women lived in cities and towns. Less than one third (30.47%) of the elderly women would exercise regularly. Only 9.66% of the samples would smoke and drink. 45.48% of the elderly women are satisfied with their current health status.
Table 1 Descriptive statistics.
varname
|
Full Sample Mean/%
|
Rural Sample
|
Urban Sample
|
Mean-Diff
|
T-Value
|
obs
|
mean
|
obs
|
mean
|
Dependent variable
|
Disability state (1=yes)
|
25.80%
|
1981
|
23.90%
|
2705
|
27.20%
|
-0.032**
|
-2.509
|
Independent variable
|
Number of births
|
4.10
|
1664
|
4.431
|
2403
|
3.865
|
0.567***
|
8.647
|
Age at first birth
|
22.91
|
1606
|
22.565
|
2329
|
23.145
|
-0.580***
|
-4.435
|
Age at last birth
|
34.26
|
1568
|
35.365
|
2255
|
33.488
|
1.877***
|
8.303
|
Childbearing period
|
11.43
|
1567
|
12.839
|
2253
|
10.449
|
2.390***
|
9.914
|
Birth interval
|
2.59
|
1564
|
2.785
|
2248
|
2.461
|
0.324***
|
6.271
|
Control variables
|
Nationality (1=Han)
|
94.36%
|
1685
|
92.40%
|
2426
|
95.70%
|
-0.033***
|
-4.533
|
Age
|
84.57
|
1977
|
84.998
|
2705
|
84.260
|
0.738**
|
2.181
|
Residence (1=Urban)
|
57.73%
|
1981
|
|
2705
|
|
|
.
|
Exercise (1=yes)
|
30.47%
|
1914
|
23.90%
|
2632
|
35.30%
|
-0.114***
|
-8.292
|
Smoking and drinking (1=yes)
|
9.66%
|
1886
|
9.50%
|
2584
|
9.80%
|
-0.002
|
-0.233
|
Health satisfaction
|
2.58
|
1932
|
2.602
|
2670
|
2.572
|
0.030
|
1.116
|
Life satisfaction
|
2.09
|
1937
|
2.145
|
2671
|
2.047
|
0.098***
|
4.192
|
Quality of sleep
|
2.58
|
1923
|
2.617
|
2654
|
2.559
|
0.058*
|
1.956
|
healthcare knowledge (1=yes)
|
41.03%
|
1871
|
39.00%
|
2621
|
42.50%
|
-0.034**
|
-2.317
|
Total family income(ln)
|
9.89
|
1838
|
9.480
|
2586
|
10.183
|
-0.703***
|
-13.987
|
a * p < 0.10, ** p < 0.05, *** p < 0.01.
3.2 Regression results
Table 2 reports the logistic regression results of the impact of number of births on the disability state of elderly women. Model 1 shows that for each additional birth in the full sample, the odds ratio of maternal disability in later life decreases by 4.3% and the result is significant at the 5% level. Model 2 shows that for each additional birth in the sample of less than 5 children, the odds ratio of maternal disability in later life decreases by 10.2% and the result is significant at the 5% level. Model 3 shows that when the number of births is 5 or more, the odds ratio of maternal disability decreases by 6.6% for each additional child, but the result is not statistically significant. Therefore, the more number of births will reduce the risk of disability of the elderly women in China to a certain extent, mainly reflected in the group of mother with less than 5.
As for other control variables, according to model 1, the odds ratio of maternal disability will increase by 10.4% when the age increases by one year, and the result is significant at the level of 1%, compared with the elderly women living in rural areas, the odds ratio of disability of urban mothers will increase by 26.5%, the odds ratio of mothers who exercise regularly will be significantly reduced by 31.1%, while that of mothers who smoke and drink will be increased by 3%.
Table 2 Estimates of the effect of number of births on disability in older women
|
Model 1
|
Model 2
|
Model 3
|
Coefficient
|
Odds Ratio
|
Coefficient
|
Odds Ratio
|
Coefficient
|
Odds Ratio
|
Number of births
|
-0.044**
|
0.957**
|
|
|
|
|
(0.022)
|
(0.021)
|
|
|
|
|
Number of births
(less than 5)
|
|
|
-0.107**
|
0.898**
|
|
|
|
|
(0.053)
|
(0.048)
|
|
|
Number of births
(5 and more)
|
|
|
|
|
-0.068
|
0.934
|
|
|
|
|
(0.049)
|
(0.044)
|
Nationality
|
0.462*
|
1.587*
|
0.359
|
1.432
|
0.565*
|
1.759*
|
(0.236)
|
(0.335)
|
(0.346)
|
(0.427)
|
(0.318)
|
(0.531)
|
Age
|
0.099***
|
1.104***
|
0.093***
|
1.098***
|
0.111***
|
1.118***
|
(0.005)
|
(0.005)
|
(0.006)
|
(0.006)
|
(0.009)
|
(0.009)
|
Residence
|
0.235**
|
1.265**
|
0.337***
|
1.401***
|
0.102
|
1.107
|
(0.093)
|
(0.118)
|
(0.130)
|
(0.184)
|
(0.136)
|
(0.151)
|
Exercise
|
-0.372***
|
0.689***
|
-0.398***
|
0.672***
|
-0.362**
|
0.696**
|
(0.110)
|
(0.075)
|
(0.143)
|
(0.095)
|
(0.177)
|
(0.119)
|
Smoking and drinking
|
0.029
|
1.030
|
-0.243
|
0.784
|
0.355
|
1.426
|
(0.148)
|
(0.151)
|
(0.213)
|
(0.166)
|
(0.218)
|
(0.302)
|
Health satisfaction
|
0.319***
|
1.375***
|
0.234***
|
1.264***
|
0.436***
|
1.547***
|
(0.060)
|
(0.081)
|
(0.080)
|
(0.099)
|
(0.096)
|
(0.142)
|
Life satisfaction
|
-0.156**
|
0.856**
|
-0.096
|
0.908
|
-0.254**
|
0.776**
|
(0.068)
|
(0.057)
|
(0.092)
|
(0.080)
|
(0.105)
|
(0.081)
|
Quality of sleep
|
-0.045
|
0.956
|
-0.009
|
0.991
|
-0.108
|
0.898
|
(0.048)
|
(0.046)
|
(0.064)
|
(0.063)
|
(0.075)
|
(0.066)
|
Healthcare knowledge
|
0.149*
|
1.160*
|
0.201*
|
1.222*
|
0.049
|
1.051
|
(0.089)
|
(0.104)
|
(0.120)
|
(0.147)
|
(0.136)
|
(0.144)
|
Total family income
|
0.050*
|
1.051*
|
-0.010
|
0.990
|
0.096**
|
1.101**
|
(0.028)
|
(0.029)
|
(0.041)
|
(0.041)
|
(0.037)
|
(0.042)
|
N
|
3545
|
3545
|
2187
|
2187
|
1358
|
1358
|
a * p < 0.10, ** p < 0.05, *** p < 0.01, b standard errors are reported in parentheses.
3.3 Heterogeneity analysis
Due to the possible differences in the impact of fertility behaviors on the health of Chinese men and women and the obvious characteristics of the urban-rural dual structure of Chinese society, this part will further investigate the relationship between number of births and disability risk to test whether there are urban-rural differences and gender differences. The results are shown in table 3 and table 4.
According to the results in the previous section, a high number of births significantly reduces the risk of disability among elder women, and this conclusion is also applicable in the urban sample. Model 4 shows that for every increase in the number of births, the odds ratio of disability of urban mothers will decrease by 0.8%, and the result is significant at the level of 1%. However, different result is found and not significant in the impact of the number of births on rural mothers. Model 5 shows that for every increase in the number of births, the odds ratio of disability will increase by 0.4%.
Table 3 Urban-rural differences in the effect of number of births on disability in elder women
|
Model 4
|
Model 5
|
|
Coefficient
|
Odds Ratio
|
Coefficient
|
Odds Ratio
|
Number of births
|
-0.080***
|
0.992***
|
0.004
|
1.004
|
(0.028)
|
(0.026)
|
(0.035)
|
(0.034)
|
Nationality
|
0.496
|
1.642
|
0.428
|
1.534
|
(0.358)
|
(0.493)
|
(0.308)
|
(0.459)
|
Age
|
0.100***
|
1.105***
|
0.099***
|
1.104
|
(0.006)
|
(0.006)
|
(0.007)
|
(0.008)
|
Residence
|
-0.451***
|
0.637***
|
-0.249
|
0.780
|
(0.134)
|
(0.085)
|
(0.191)
|
(0.145)
|
Exercise
|
0.073
|
1.076
|
-0.011
|
0.989
|
(0.190)
|
(0.200)
|
(0.233)
|
(0.238)
|
Smoking and drinking
|
0.243***
|
1.275***
|
0.433***
|
1.542
|
(0.074)
|
(0.095)
|
(0.102)
|
(0.149)
|
Health satisfaction
|
-0.100
|
0.905
|
-0.238**
|
0.788
|
(0.086)
|
(0.077)
|
(0.111)
|
(0.086)
|
Life satisfaction
|
-0.071
|
0.931
|
-0.005
|
0.995
|
(0.060)
|
(0.056)
|
(0.080)
|
(0.078)
|
Quality of sleep
|
0.108
|
1.113
|
0.197
|
1.218
|
(0.114)
|
(0.128)
|
(0.146)
|
(0.179)
|
Healthcare knowledge
|
0.071*
|
1.074*
|
0.021
|
1.022
|
(0.040)
|
(0.041)
|
(0.039)
|
(0.042)
|
_cons
|
-10.734***
|
0.000***
|
-11.177***
|
0.000
|
(0.851)
|
(0.000)
|
(0.971)
|
(0.000)
|
N
|
2124
|
2124
|
1421
|
1421
|
a * p < 0.10, ** p < 0.05, *** p < 0.01, b standard errors are reported in parentheses.
Table 4 shows the gender differences in the effect of the number of births on the risk of disability. It can be seen from model 6 that for every increase in the number of births, the odds ratio of mother's disability will be significantly reduced by 4.3%, while Model 7 shows that for every increase in the number of births, the odds ratio of father's disability will be increased by 1.8%, but the result is not statistically significant.
Table 4 Gender differences in the impact of number of births on disability in elder people
|
Model 6
|
Model 7
|
|
Coefficient
|
Odds Ratio
|
Coefficient
|
Odds Ratio
|
Number of births
|
-0.044**
|
0.957**
|
0.018
|
1.018
|
(0.022)
|
(0.021)
|
(0.027)
|
(0.029)
|
Control variables
|
Yes
|
Yes
|
Yes
|
Yes
|
N
|
3545
|
3545
|
3134
|
3134
|
a * p < 0.10, ** p < 0.05, *** p < 0.01, b standard errors are reported in parentheses.
3.4 Further analysis
Existing studies have shown that, for women, in addition to the number of births, other fertility behaviors will also affect their disability risk. Therefore, this paper further examines the impact of other fertility behaviors on the risk of disability in later life.
Table 5 reports the estimated effects of age at first birth, age at last birth, childbearing period and birth interval on mothers' risk of disability in later life. Model 8 shows that for every one year addition the age that the mother gives birth to the first child, her disability risk ratio will increase by 0.3%, but the result is not significant. As shown in model 9, for every one year addition the age at last child, the odds ratio of disability will be reduced by 1.3% and the result is significant at the level of 10%. Model 10 shows that when mothers’childbearing period is extended by 1 year, the odds ratio of disability decreases by 1.1%. Model 11 shows that the longer the interval between births, the lower the risk of disability in the mother.
Table 5 Estimates of the impact of other fertility behaviours
|
Model 8
|
Model 9
|
Model 10
|
Model 11
|
Age at first birth
|
1.003
|
|
|
|
(0.011)
|
|
|
|
Age at last birth
|
|
0.987*
|
|
|
|
(0.007)
|
|
|
Childbearing period
|
|
|
0.989*
|
|
|
|
(0.007)
|
|
Birth interval
|
|
|
|
0.983
|
|
|
|
(0.029)
|
Control variables
|
Yes
|
Yes
|
Yes
|
Yes
|
N
|
3454
|
3358
|
3357
|
3349
|
a Odds ratios are reported in the table, b * p < 0.10, ** p < 0.05, *** p < 0.01.
Similarly, we further investigate the differences between urban and rural areas and the results are shown in Table 5. Models 12 and 16 show the effect of age at first birth on the risk of maternal disability in later life, with a 0.7% increase in the odds ratio for urban mothers and a 0.6% decrease in the odds ratio for rural mothers for each year of delay in the first birth, but this result is not significant. Model 13 and Model 17 show that when giving birth to the last child, every subsequent one year postponed, the odds ratio of disability for mothers living in cities and towns will decrease by 1.7%, while the odds ratio for rural mothers will decrease by 0.8% but the result is not statistically significant. The results of model 14 show for each additional year of childbearing period for urban mothers, the risk of disability is reduced by 1.7% and this finding applies equally to the sample of rural women. According to Model 15 and Model 19, the results show that the longer the interval between having children, the lower the mother’s risk of disability.
Table 6 Urban-rural differences in the impact of other fertility behaviours
|
Urban
|
Rural
|
|
Model 12
|
Model 13
|
Model 14
|
Model 15
|
Model 16
|
Model 17
|
Model 18
|
Model 19
|
Age at first birth
|
1.007
|
|
|
|
0.994
|
|
|
|
(0.013)
|
|
|
|
(0.018)
|
|
|
|
Age at last birth
|
|
0.983*
|
|
|
|
0.992
|
|
|
|
(0.009)
|
|
|
|
(0.012)
|
|
|
Childbearing period
|
|
|
0.983*
|
|
|
|
0.996
|
|
|
|
(0.009)
|
|
|
|
(0.012)
|
|
Birth interval
|
|
|
|
0.992
|
|
|
|
0.967
|
|
|
|
(0.036)
|
|
|
|
(0.053)
|
Control variables
|
Yes
|
Yes
|
Yes
|
Yes
|
Yes
|
Yes
|
Yes
|
Yes
|
N
|
2070
|
2005
|
2004
|
1999
|
1384
|
1353
|
1353
|
1350
|
a Odds ratios are reported in the table, b * p < 0.10, ** p < 0.05, *** p < 0.01.