The authors have declared that no competing interests exist.
Conceived and designed the experiments: YW DH HJW HZ FY. Performed the experiments: YW DH HJW HZ FY. Analyzed the data: HZ LZ FY YJH. Contributed reagents/materials/analysis tools: LZ YJH AQW. Wrote the paper: HZ LZ FY DH YJH AQW SQL YW.
To examine the effects of maternal death on the health of the index child, the health and educational attainment of the older children, and the mental health and quality of life of the surviving husband.
A cohort study including 183 households that experienced a maternal death matched to 346 households that experienced childbirth but not a maternal death was conducted prospectively between June 2009 and October 2011 in rural China. Data on household sociodemographic characteristics, physical and mental health were collected using a quantitative questionnaire and medical examination at baseline and follow-up surveys. Multivariate linear regression, logistic regression models and difference-in-difference (DID) were used to compare differences of outcomes between two groups.
The index children who experienced the loss of a mother had a significantly higher likelihood of dying, abandonment and malnutrition compared to children whose mothers survived at the follow-up survey. The risk of not attending school on time and dropping out of school among older children in the affected group was higher than those in the control group during the follow-up. Husbands whose wife died had significantly lower EQ-5D index and EQ-VAS both at baseline and at follow-up surveys compared to those without experiencing a wife’s death, suggesting an immediate and sustained poorer mental health quality of life among the surviving husbands. Also the prevalence of posttraumatic stress disorder (PTSD) was 72.6% at baseline and 56.2% at follow-up among husbands whose wife died.
Maternal death has multifaceted and spillover effects on the physical and mental health of family members that are sustained over time. Programmes that reduce maternal mortality will mitigate repercussions on surviving family members are critical and needed.
China has made tremendous progress in decreasing maternal mortality rates (MMRs) in the past 25 years [
There is a consensus that the loss of a mother is not just a grievous single event to the family, but that has large and negative effects on the surviving children, spouse, families and communities [
Previous studies undertaken in Africa (described above), have begun to investigate the influence of maternal death on outcomes of children, especially the well-established connection between a maternal death and survival of the index children at their early stage of life. However, generalizability of study results may be limited due to localized cultural effects and being compounded by the high HIV prevalence in some settings. Very little is known on the lasting effects on the index children and their families, particularly the surviving husband. Also, qualitative studies on educational attainment among the older children who experienced the loss of a mother may not sufficient to detect the extent to which their school performances are effected by the loss of their mother.
This study aimed to explore wide-ranging impacts of maternal death on index children, older children and husbands in the context of relatively low MMRs in China.
The study was approved by the ethical reviews boards at Peking University and the World Health Organization. Signed informed consent for all caregivers/guardians on behalf of themselves and minor children were obtained prior to any interviews. All the interviews were conducted without any incentives, and timed to take place after an appropriate grieving period had passed.
Details regarding the study design have been described elsewhere [
Based on inclusion criteria below [
Inclusion criteria for affected group:
Having a maternal death within 3 months before the interview; a woman who died during late pregnancy (≥28 gestational weeks) or within 42 days after giving birth was defined as maternal death, excluding causes not attributable to the pregnancy.
Matching criteria for control group:
Experiencing childbirth within 3 months before the interview, and;
Dwelling in the same village and;
Having comparable economic status estimated by the village leaders and;
Having the same household type prior to maternal death (with or without older children; nuclear or extended family) and;
Having the same ethnicity, if possible.
A total of 530 households who experienced a maternal death were recorded by the CMCHO in selected provinces during the study period. Of them, 40.9% (217/530) were excluded due to not meeting the inclusion criteria (primarily due to the maternal death occuring prior to 28 gestational weeks). Of the 313 households that met the inclusion criteria, 37.6% (118/313) refused to participate in the study because of their grief. This left 195 households to be interviewed in the affected group, accounting for 62.3% of the eligible participants. A total 384 households who experienced childbirth but not a maternal death were selected as a matching control group of the affected households. This resulted in a ratio of 2:1 control: affected study group; it is noted that 6 households in the affected group were matched by the control group in the ratio of 1:1 because they lived in the remote areas with few residents. During the follow-up, 183 households in the affected group and 346 households in the control group completed the survey. The present study only considered these 529 households who completed both baseline and follow-up surveys.
The baseline and follow-up surveys applied same measurement tools to collect the data. The caregivers of the children were chosen as respondents to answer questions regarding children. Questions regarding husbands had to be answered by the husbands.
The questionnaire included questions pertaining to the household socio-demographic characteristics (age, gender, ethnicity, household size, etc.), whether the child had diarrhea or cough in the past two weeks, as well as questions concerning the educational attainment for the older children to the present). Body length for children aged under 24 months and height for children aged 24 to 59 months (Wujin Weighing Apparatus Factory, Changzhou, China), and weight for all the children aged 0 to 59 months (TH Leaguer Sensory Technology company, Shenzhen, China) were measured. Each measurement was conducted twice and the mean value were obtained. Raw data were converted to Z-score and categorized to indicate the status of child nutrition: stunting was defined as Z-score of length/height-for-age below -2; underweight was defined as Z-score of weight-for-age below -2; wasting was defined as Z-score of weight-for-height below -2. Malnutrition was defined as presence of any of these adverse nutritional statuses (a Z-score below -2) [
In addition, information was collected to assess the mental health and the quality of life of husbands who experienced a maternal death. Breslau’s 7-item screening scale was adopted to evaluate the husbands’ posttraumatic stress disorder (PTSD) [
The demographic characteristics were compared between the affected and control groups, using Chi-square and the Wilcoxon tests.
For children, each of eight binary outcomes, including stunting, underweight, wasting, malnutrition, having diarrhea in the past two weeks, having cough in the past two weeks, not attending school and dropping out of school was compared between two groups using logistic regression models with adjusting for child’s age, father’s age, father’s education and household income. To measure the change from baseline to follow-up between the affected and control groups, we used multivariate regression and logistic regression models with interaction terms of survey time (follow-up vs. baseline) and group (affected vs. control group).
For binary outcomes, the difference-in-difference (DID) is estimated by the interaction terms and interpreted as the ratio of the odds ratio (
The following model was employed for binary outcomes:
The following model was employed for continuous outcomes:
In addition, to examine whether the attrition rate had an impact on the estimate of main outcomes, a sensitivity analysis using inverse probability weighting was conducted. The 95% confidence intervals (excluding 1) for the ratio of odds ratio represent statistically significant DID for binary outcomes. The 95% confidence intervals (excluding 0) for the difference of difference in means represent statistically significant effects for continuous outcomes. The threshold significant level was set at p < 0.05. Epidata3.1 software package was used to input data. The SPSS 20.0 for Windows statistical software package was used in present study.
As shown in
The figure represents selection of study participants in both groups from pre-baseline (end of the delivery) to baseline and follow-up. The primary reason of loss to follow-up for husbands is they went out for work during surveys. Index children in the affected group had a higher rate of death and abandonment than control group during pre-baseline and follow-up periods.
Variables | Affected group | Control group | ||||
---|---|---|---|---|---|---|
Responders | Non-responders | Total | Responders | Non-responders | Total | |
Age (Month) (median, IQR) | 3 [2, 4] | - | 3 [2, 4] |
2 [2, 3] | - | 2 [2, 3] |
Gender (%, n/N) | ||||||
Male | 45.4% (49/108) | - | 45.4% (49/108) | 47.6% (169/355) | - | 47.6% (169/355) |
Female | 54.6% (59/108) | - | 54.6% (59/108) | 52.4% (186/355) | - | 52.4% (186/355) |
Age (Month) (median, IQR) | 74 [51, 112] | - | 74 [51, 112] |
65 [42, 91] | - | 65 [42, 91] |
Gender (%, n/N) | ||||||
Male | 51.9% (55/106) | - | 51.9% (55/106) | 47.8% (97/203) | - | 47.8% (97/203) |
Female | 48.1% (51/106) | - | 48.1% (51/106) | 52.2% (106/203) | - | 52.2% (106/203) |
Age (Years) (median, IQR) | 33 [27, 39] |
29 [26, 33] | 30 [27, 36] |
28 [24, 32] | 28 [24, 32] | 28 [24, 32] |
Ethnicity (%, n/N) | ||||||
Han | 76.2% (64/84) | 83.8% (83/99) | 80.3% (147/183) | 63.5% (61/96) |
86.4% (216/250) | 80.1% (277/346) |
Minorities |
23.8% (20/84) | 16.2% (16/99) | 19.7% (36/183) | 36.5% (35/96) | 13.6% (34/250) | 19.9% (69/346) |
Education (%, n/N) | ||||||
Illiterate | 4.8% (4/84) |
5.1% (5/99) | 4.9% (9/183) |
2.1% (2/96) |
0.8% (2/250) | 1.2% (4/346) |
Primary | 58.3% (49/84) | 28.3% (28/99) | 42.1% (77/183) | 43.8% (42/96) | 29.2% (73/250) | 33.2% (115/346) |
Secondary or higher | 36.9% (31/84) | 66.7% (66/99) | 53.0% (97/183) | 54.2% (52/96) | 70.0% (175/250) | 65.6% (227/346) |
Number of children | ||||||
1 | 28.6% (24/84) |
43.4% (43/99) | 36.6% (67/183) | 39.6% (38/96) | 42.4% (106/250) | 41.6% (144/346) |
2 or more | 71.4% (60/84) | 56.6% (56/99) | 63.4% (116/183) | 60.4% (58/96) | 57.6% (144/250) | 58.4% (202/346) |
Household size (%, n/N) | ||||||
1–5 | 90.5% (76/84) a | 72.7% (72/99) | 80.9% (148/183) | 78.1% (75/96) | 77.2% (193/250) | 77.5% (268/346) |
6+ | 9.5% (8/84) | 27.3% (27/99) | 19.1% (35/183) | 21.9% (21/96) | 22.8% (57/250) | 22.5% (78/346) |
Nuclear families (%, n/N) | ||||||
Yes | 48.8% (41/84) |
18.2% (18/99) | 32.2% (59/183) | 33.3% (32/96) | 30.4% (76/250) | 31.2% (108/346) |
No | 51.2% (43/84) | 81.8% (81/99) | 67.8% (124/183) | 66.7% (64/96) | 69.6% (174/250) | 68.8% (238/346) |
Income (median, IQR) | 3131 [2278, 4828] | 3585 [2194, 5325] | 3379 [2250, 5112] |
4149 [2571, 6597] |
4899 [3210, 7553] | 4737 [2991, 7496] |
Expenditure (median, IQR) | 3952 [2504, 7346] | 4773 [2643, 7211] | 4132 [2523, 7217] |
4852 [3125, 8188] | 5212 [3174, 8584] | 5070 [3164, 8554] |
Affected group: households who experienced a maternal death; control group: households who had childbirth but not a maternal death
a. significantly different from non-responders in affected group (p<0.05)
b. significantly different from the control group (p<0.05)
c. significantly different from non-responders in control group (p<0.05)
d. In China, “minority” means non-Han ethnicity, including Hui, Yi, Hani, etc.
At the baseline, the prevalence of malnutrition among the index children in the affected group and control group was 40.0% and 14.5%, respectively (
Outcomes | Baseline | Follow-up | DID | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Affected n(%) | Control n(%) | OR (95%CI) | Affected n(%) | Control n(%) | OR (95%CI) | Adjusted |
Adjusted |
||||
Unadjusted | Adjusted |
Unadjusted | Adjusted |
Affected | Control | ||||||
28 | 29 | 5.1 | 5.0 | 27 | 64 | 1.9 | 1.7 | 1.0 | 3.0 | 0.3 | |
(32.9%) | (8.8%) | (2.8–9.3) | (2.6–9.4) | (32.5%) | (20.4%) | (1.1–3.2) | (0.9–3.0) | (0.5–1.9) | (1.8–4.9) | (0.1–0.8) | |
16 | 13 | 5.6 | 5.1 | 7 | 19 | 1.4 | 1.0 | 0.4 | 1.6 | 0.2 | |
(18.8%) | (3.9%) | (2.6–12.5) | (2.3–11.7) | (8.4%) | (6.0%) | (0.5–3.4) | (0.4–2.6) | (0.1–0.9) | (0.8–3.4) | (0.1–0.8) | |
5 | 16 | 1.2 | 1.4 | 2 | 4 | 1.9 | 0.9 | 0.4 | 0.3 | 1.6 | |
(5.9%) | (4.8%) | (0.4–3.2) | (0.4–3.8) | (2.4%) | (1.3%) | (0.3–10.1) | (0.1–5.7) | (0.1–1.9) | (0.1–0.7) | (0.2–11.3) | |
34 | 48 | 3.9 | 4.1 | 28 | 69 | 1.8 | 1.6 | 0.7 | 1.8 | 0.4 | |
(40.0%) | (14.5%) | (2.3–6.7) | (2.3–7.2) | (33.7%) | (22.0%) | (1.1–3.0) | (0.9–2.8) | (0.4–1.4) | (1.2–2.7) | (0.2–0.9) | |
20 | 64 | 1.0 | 1.0 | 19 | 60 | 1.0 | 1.0 | 0.9 | 0.9 | 1.0 | |
(18.5%) | (18.0%) | (0.6–1.8) | (0.6–1.8) | (17.6%) | (16.9%) | (0.6–1.8) | (0.5–1.7) | (0.5–1.9) | (0.6–1.4) | (0.5–2.3) | |
21 | 63 | 1.1 | 1.1 | 34 | 113 | 1.0 | 1.0 | 1.9 | 2.2 | 0.9 | |
(19.4%) | (17.7%) | (0.6–1.9) | (0.6–2.0) | (31.5%) | (31.9%) | (0.6–1.6) | (0.6–1.6) | (1.0–3.7) | (1.5–3.1) | (0.4–1.8) |
Affected group: households who experienced a maternal death; control group: households who had childbirth but not a maternal death
a. Adjusted for child’s age, father’ age and education, and household income.
At follow-up, only two older children (1.8%) in affected group were abandoned and being cared for by relatives, as shown in
As shown in
Outcomes | Baseline | Follow-up | DID | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Affected n(%) | Control n(%) | OR (95%CI) | Affected n(%) | Control n(%) | OR (95%CI) | Adjusted |
Adjusted |
||||
Unadjusted | Adjusted |
Unadjusted | Adjusted |
Affected | Control | ||||||
8 | 23 | 0.9 | 0.7 | 5 | 12 | 1.0 | 0.9 | 0.5 | 0.5 | 1.1 | |
(21.6%) | (24.2%) | (0.3–2.1) | (0.3–1.9) | (13.5%) | (14.0%) | (0.3–2.8) | (0.3–3.3) | (0.1–1.9) | (0.2–1.0) | (0.3–5.0) | |
3 | 7 | 1.1 | 0.7 | 2 | 4 | 1.2 | 0.8 | 0.6 | 0.6 | 1.0 | |
(8.1%) | (7.4%) | (0.2–4.2) | (0.1–3.7) | (5.4%) | (4.7%) | (0.2–6.3) | (0.1–5.9) | (0.1–4.4) | (0.2–2.4) | (0.1–10.0) | |
0 | 2 | - | - | 0 | 0 | - | - | - | - | - | |
(0.0%) | (2.1%) | (0.0%) | (0.0%) | ||||||||
8 | 24 | 0.8 | 0.7 | 6 | 12 | 1.2 | 1.2 | 0.7 | 0.4 | 1.5 | |
(21.6%) | (25.3%) | (0.3–2.0) | (0.3–1.9) | (16.2%) | (14.0%) | (0.4–3.4) | (0.3–4.0) | (0.2–2.3) | (0.2–1.0) | (0.4–6.3) | |
8 | 13 | 1.1 | 1.2 | 6 | 11 | 1.0 | 0.9 | 0.7 | 0.8 | 0.9 | |
(7.5%) | (6.7%) | (0.4–2.8) | (0.5–3.2) | (5.7%) | (5.7%) | (0.3–2.7) | (0.3–2.7) | (0.2–2.2) | (0.4–1.9) | (0.2–3.5) | |
34 | 43 | 1.7 | 2.0 | 29 | 27 | 2.3 | 2.2 | 0.8 | 0.6 | 1.4 | |
(32.1%) | (22.2%) | (1.0–2.8) | (1.1–3.5) | (27.6%) | (14.0%) | (1.3–4.3) | (1.2–4.2) | (0.4–1.5) | (0.3–1.0) | (0.6–3.1) | |
3 | 3 | 1.7 | 2.8 | 6 | 2 | 5.4 | 6.8 | 2.4 | 0.6 | 3.4 | |
(4.3%) | (2.7%) | (0.3–8.5) | (0.5–16.3) | (8.8%) | (1.8%) | (1.1–27.4) | (1.2–37.4) | (0.6–12.9) | (0.1–4.2) | (0.3–35.0) | |
3 | 2 | 2.5 | 3.5 | 5 | 2 | 4.4 | 9.0 | 1.9 | 1.0 | 1.8 | |
(4.3%) | (1.8%) | (0.4–19.5) | (0.5–24.1) | (7.4%) | (1.8%) | (0.8–23.4) | (1.4–56.2) | (0.4–10.0) | (0.1–7.5) | (0.1–22.5) |
Affected group: households who experienced a maternal death; control group: households who had childbirth but not a maternal death
a. Adjusted for child’s age, father’ age and education, and household income.
The attrition rates for the husbands of the affected group at baseline and follow-up survey were 38.2% (70/183) and 15.8% (29/183), respectively. In the control group, the attrition rates at baseline and follow-up survey were 58.9% (204/346) and 13.2% (46/346), respectively. The main reasons for loss to follow-up were that the husbands were working outside or not at home at the time of the survey. The husbands in the affected group were more likely to be older, illiterate and have lower income than those in the control group.
The results of quality of life for husbands are shown in
Outcomes | Baseline | Follow-up | DID | ||||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Affected (mean±SD) | Control (mean±SD) | Affected vs. Control Difference of Mean (95% CI) | Affected (mean±SD) | Control (mean±SD) | Affected vs. Control Difference of Mean (95% CI) | Follow-up vs. Baseline Adjusted |
Adjusted |
||||
Unadjusted | Adjusted |
Unadjusted | Adjusted |
Affected | Control | ||||||
EQ-5D index | 0.73±0.07 | 0.82±0.05 | -0.09 | -0.09 | 0.78±0.07 | 0.83±0.04 | -0.05 | -0.04 | 0.05 | 0.01 | 0.04 |
(-0.11 –-0.08) | (-0.11 –-0.08) | (-0.07 –-0.03) | (-0.06 –-0.02) | (0.03–0.07) | (-0.01–0.02) | (0.02–0.07) | |||||
EQ-VAS | 50.1±21.1 | 83.1±14.7 | -33.0 | -31.7 | 63.8±21.4 | 81.5±13.4 | -17.8 | -15.1 | 14.0 | -1.2 | 15.6 |
(-37.4 –-28.6) | (-36.4 –-26.9) | (-23.0 –-12.6) | (-20.7 –-9.4) | (8.0–20.0) | (-4.9–2.4) | (8.9–22.4) |
Affected group: households who experienced a maternal death; control group: households who had childbirth but not a maternal death
a. Adjusted for husbands’ age and education, and household income.
Further analysis in each dimension of EQ-5D found that about 90% of the affected husbands at baseline had anxiety or depression (
The black and gray bars represent husbands in the affected group, and the other two bars represent those from the control group. In each domain of EQ-5Q, the higher score, the worse outcome it indicates.
In addition, Posttraumatic Stress Disorder (PTSD) screening showed a significant decline from 4.71±2.00 at baseline to 3.85±2.00 at follow-up (p = 0.004) and the prevalence of PTSD decreased from 72.6% at baseline to 56.2% at follow-up (p<0.001) among husbands in the affected group, indicating the symptoms were modestly alleviated and the number of cases decreased during follow up period.
Our study found a relatively death rate (11.6%, 14/120) among index children within 15 months after maternal death, most of whom (85.7%, 12/14) died within 3 months after maternal death. This added evidence that maternal death was associated with elevated risk of dying at early stage among index children [
First, early termination of breastfeeding makes babies vulnerable to malnutrition, which may contribute to the increased risk of infections or death [
Of note, our study also found that the prevalence of stunting, underweight and malnutrition among index children in the control group at follow-up survey was higher than at baseline. This may relate to inappropriate feeding practices adopted by caregivers in rural settings in China. Zhou and his colleagues found that the prevalence of stunting among children aged 6–36 months increased with age and the prevalence peaked at 25.4% among children aged 24–35 months in seven poor counties of China [
Our results showed that the risk of not attending school on time and dropping out of school among older children in the affected households was higher than those in the control households at follow-up survey. This may derive from psychological vulnerability and bereavement reactions after experiencing the loss of a mother [
Our study also found a significant poorer quality of life of husbands in the affected group compared to those in the control groups. According to National Health Services Survey (NHSS) of China in 2008, the mean VAS score of 58,163 men (aged 15–103) was 80.9 [
Furthermore, our study found that over half of the affected husbands had a probability of having PTSD one year after maternal death. For husbands who experienced a maternal death in present study, PTSD may be result from not only the sudden loss of their wife, but also financial problems, additional caregiving responsibilities and coping with hardship in the family [
There are several limitations in our study. First, a high and different rate of loss to follow-up for husbands between the affected and control groups due to working outside home was seen. This might affect internal validity of estimates. More husbands in the affected group had to stay at home and take care of babies during the follow-up period, and more husbands in the control group went out for working in large cities, commonly practiced by families in rural China. Second, the absence of time trade-off (TTO) integrating conversion of EQ-5D for Chinese made it necessary to use a Japanese conversion. The difference between Chinese and Japanese is unknown, although researchers conducted a study demonstrating that the EQ-5D utility index is valid in Asian population [
In conclusion, our study demonstrates wide-ranging and spillover effects of maternal death on the physical and mental health of living children and husbands. Further reduction in the burden of maternal mortality is critical, and a public health attention should be paid to family members following a maternal death.
(XLS)
We want to thank research teams from Hebei, Henan, and Yunnan provinces for their hard work in orchestrating the field work and the support from the Chinese Ministry of Health and Provincial Health Offices in assistance with identifying study population through the registration system. We also want to thank all of family members who participated in this study and expressed our condolences to those who experienced the loss of their loved one. We are grateful for endeavors from each member in Economic Impact of Maternal Deaths study, including Yan Wang (principal investigator), Hai-Jun Wang, Fang Ye, Hong Zhou, Chu-Yun Kang, Shan-Shan Hou, Du Wang, Deng Ao, Yao Feng, Yi-Chong Xu (Division of Maternal and Child Health, School of Public Health, Peking University), Jin-Hua Li, Hai-Ying Ma (Hebei Women and Children Health Center) in Hebei; Mei-Lin Yao, Feng-Zhi You, Wei-jie Zhang, Hui-Min Qu, Xiao-Hui Xu, Rui Wang, Jian Liu, Wen-Bin Jia, De-Qi Du, Jie Deng (Women's healthcare section, Zheng-zhou University 3rd Affiliated Hospital) in Henan; Yan Li, Wen-Long Cui, Ying Huang, Jing Long, Hai-Mei Hu, Shi-Hong Xu, Jun-Ying Wang, Hai-Xia Yang, Ying Tan, Gui-Cun Chen, Xi-Ying Luo (School of Public Health, Kunming Medical College); Ya-Ping Zhu, Hong Zhou, Tao Zhao, Wei Li, Guang-Ping Guo (Maternal and Child Health Hospital of Yunnan) in Yunnan. We acknowledge Robert Black for providing intellectual suggestions on the revision of manuscript.
The interpretation of results in this study is solely attributable to the authors and does not reflect the official view of the World Health Organization or the Peking University School of Public Health.