Large cohort studies on relationship between family history of stroke (FHS) and stroke risk are lacking in Asians. We aimed to systematically evaluate the association of FHS with stroke risk in a cohort study of 0.5 million Chinese adults.
Information about FHS was self-reported. The median follow-up time was 7.16 years and the end-point of follow-up was incident stroke, which was entered directly into the China Kadoorie Biobank system. Multivariate analyses were performed with Cox proportional hazards model, and interaction analyses were carried using likelihood-ratio tests.
Compared with participants without FHS, the hazard ratio (HR) (95% confidence interval, CI) of stroke for participants with FHS was 1.50 (1.46-1.55). The HRs increased with the number of first degree relatives with stroke (HRs=1.41, 1.98 and 2.47 for 1, 2 and ≥3 relatives, respectively,
FHS is an independent risk factor for stroke in Chinese. The more first degree relatives are affected by stroke, the higher are individuals’ risk of suffering from stroke. The management of the health-risk behaviors for reducing stroke should be highlighted, especially for the individuals with FHS.
Stroke is the second most frequent cause of death worldwide [
One convenient way to determine the individuals with potential risks for stroke is to collect family history information. Regularly updating family histories was recommended by the 2002 American Heart Association guidelines for primary prevention of cardiovascular disease [
The differences have been reported between different types of FHS (maternal, paternal, and sibling history) in relationship with incident stroke [
Therefore, we intend to systematically evaluate the relationship between FHS and incident stroke in a large-scale, Chinese population-based cohort study.
This study was based on the China Kadoorie Biobank (CKB, known previously as the Kadoorie Study of Chronic Disease in China [KSCDC]). The study rationale, design, survey methods, and baseline population characteristics of the CKB study have been previously described in detail [
Ethical approval for our study was obtained from Central Ethical Committee of the Chinese Center for Disease Control and Prevention (Beijing, China), and the Oxford Tropical Research Ethics Committee, the University of Oxford (UK). All participants provided written informed consent.
The end point during the follow-up was incident stroke, including mortality and morbidity data. The vital status of study participants was ascertained through linkage with local disease surveillance points system death certificates and official residential records. Any deaths occurred were coded by trained staff “blinded” to baseline information. Causes of death provided by official death certificates were supplemented, if necessary, separate active confirmation could be carried out by reviewing medical records, reviewing residential records, visiting local communities, or directly contacting participants. Besides, linkage to a local health insurance database was also an important supplementary way of ascertaining deaths. For any additional deaths not verified by routine procedures, the causes could be identified through reviewing hospital records or conducting a verbal autopsy. Information on non-fatal stroke was collected by means of linkage with the established disease registries, as well as the national health insurance claim databases. In addition, participants who failed to be included in the health insurance system were followed annually by trained staff to ascertain their status including hospital admission, disease development, migration and death.
Incident strokes were coded as ischemic stroke (I63), hemorrhagic stroke (subarachnoid [I60] or intracerebral [I61]) and other or unknown stroke type (I64) by trained staff “blinded” to baseline information (using the 10th International Classification of Diseases, ICD-10). Besides, stroke cases were further reviewed by a group of professional neurologists according to uniform and standardized diagnostic criteria. Follow-up time was calculated for each participant from the date of the start of study until the date of the occurrence of stroke, loss to follow-up, or the end of follow-up (December 31, 2013), whichever occurred first.
In the baseline questionnaire, each subject was asked by the interviewer whether the family member (father, mother, or siblings) had been affected by stroke. For siblings, the number of affected members with stroke was recorded. We defined a participant as “family history positive” if he or she reported that one parent or sibling had stroke. Positive parental history was defined as reporting a positive history for either or both parents. In this study, first degree relatives included fathers, mothers, and siblings. For each subject, the first degree family members’ stroke history had been collected.
All participants completed the standardized questionnaires covering detailed questions on general socioeconomic and demographic status, health status and medical history (hypertension, diabetes, stroke or transient ischemic attack, cancer and heart disease), smoking status, alcohol consumption, and other lifestyle behaviors. Variables involving general socioeconomic and demographic status included age, sex, residential area, occupation, etc. The level of physical activity was calculated as metabolic equivalent task hours daily (metabolic equivalent of task-hours/day). Besides, the number of siblings was covered.
Physical measurements were made by trained staff using calibrated instruments including body height, weight, waist and hip circumference, heart rate and blood pressure. Body mass index was calculated as weight (kg) divided by the square of height (m2). Prevalent diabetes was defined as measured fasting blood glucose 37.0 mmol/L, measured random blood glucose 311.1 mmol/L, or self-reported diagnosis of diabetes. Prevalent hypertension was defined as measured systolic blood pressure 3,140 mm Hg, measured diastolic blood pressure 390 mm Hg, self-reported diagnosis of hypertension, or self-reported use of antihypertensive agents at baseline.
Continuous data were presented as mean (standard deviation) and categorical variables as counts and frequencies. We compared means by the method of Student’s t-test, and categorical variables were compared using Pearson’s
Stratified analyses were carried on: age (<45, 45 to 54, 55 to 64, or 365 yr), gender (male or female), marital status (married or widowed/separated/divorced/never married), residential area (rural or urban), education (Illiteracy/primary school or middle school and above), smoking status (current regular smoker or not), alcohol consumption (current regular drinker or not), physical activity (categorized using median), BMI (<24.0, 24.0 to 27.9, or 328.0), and prevalent hypertension and diabetes at baseline (presence or absence). The interaction analyses were performed by means of likelihood-ratio tests, comparing models with and without the interaction items between the baseline stratifying variables and FHS as a dichotomous variable.
All CIs were estimated at the 95% level. All statistical tests were two-sided and significance was defined as
Baseline characteristics of the study population were summarized in
Total person-years of follow-up were 3,338,261 and the median follow-up time was 7.16 years. A total of 26,395 (5.57%) stroke cases were reported (20,528 of ischemic stroke, 4,968 of hemorrhagic stroke and 899 of other conditions). Incidence rate of stroke per 1,000 person years was 7.31 for participants without FHS, and 10.62 for participants with FHS. Incidence rates of stroke according to the number of family members with stroke were 9.78, 15.44, and 24.29 per 1,000 person years for subjects whose FHS involving 1, 2, and ≥3 members, respectively (
The age- and gender- adjusted HR (95% CI) of stroke for participants with FHS was 1.50 (1.46-1.55) as compared with those without FHS (
The age- and gender- adjusted HRs were 1.57 (95% CI: 1.50-1.66) and 1.49 (95% CI: 1.45-1.54) for sibling history and parental history, respectively, and the difference was not statistically significant (
We further performed stratified analyses according to age groups (classified as <45, 45-54, 55-64, and ≥65 yr). We found that the HRs of incident stroke related to FHS decreased with age, and the HRs (95% CIs) were 1.60 (1.46-1.76), 1.51 (1.43-1.59), 1.25 (1.19-1.31), and 1.14 (1.08-1.21), respectively (
This Chinese cohort study showed that FHS was an independent risk factor for developing stroke, for whatever type of FHS. The more first degree relatives are affected by stroke, the higher are individuals’ risk of suffering from stroke. Maternal history of stroke and paternal history of stroke had no differential effects on the risk of stroke, in both men and women. Individuals reported a positive FHS at young age had higher risk of stoke than those at late age. Moreover, FHS interacted with the health risk behaviors (smoking status and alcohol consumption) on the risk of stroke occurrence.
FHS represents a combination of genetic factors and shared environmental factors. It has been reported that compared with parent-offspring pairs, shared environmental effects on cardiovascular risk factors were stronger within sibling pairs [
Previous studies provided evidence for that the relationship between maternal history and stroke was different from that between paternal history and stroke [
Numerous factors have been identified to be implicated with stroke occurrence in epidemiological research [
Strengths of our study are the prospective cohort design, the large sample size, the well-designed questionnaire, and the efficient data collection and management. There are also some limitations that need to be mentioned. First, we did not obtain the information about the age of onset of parental stroke. Thus, we could not explore the association of early-onset stroke in parents to incident stroke in offspring. Second, family history data were obtained based on self-report, which might affect the accuracy of the information and lead to some degree of misclassification bias. However, in self-reported surveys, the recall bias is inevitable, and in comparison with case-control studies, the recall bias was less in our cohort study. Besides, previous studies have reported that self-reported history is reliable for stroke data [
FHS is an independent risk factor for stroke in Chinese, and the more first degree relatives are affected by stroke, the higher are individuals’ risk of suffering from stroke. The management of the health risk behaviors for reducing stroke should be highlighted, especially for the individuals with FHS.
This work was supported by grant from the National Natural Science Foundation of China (81390540, 81390543). The CKB baseline survey and the first re-survey were supported by a grant from the Kadoorie Charitable Foundation in Hong Kong. The long-term follow-up is supported by grants from the UK Wellcome Trust (088158/Z/09/Z and 104085/Z/14/Z) and a grant from the Chinese Ministry of Science and Technology (2011BAI09B01). The funders had no role in the study design, data collection, data analysis and interpretation, writing of the report, or the decision to submit the article for publication.
The authors have no financial conflicts of interest.
The chief acknowledgment is to the participants, the project staff, and the China National Centre for Disease Control and Prevention (CDC) and its regional offices for assisting with the fieldwork. We thank Judith Mackay in Hong Kong; Yu Wang, Gonghuan Yang, Zhengfu Qiang, Lin Feng, Maigeng Zhou, Wenhua Zhao, and Yan Zhang in China CDC; Lingzhi Kong, Xiucheng Yu, and Kun Li in the Chinese Ministry of Health; and Sarah Clark, Martin Radley, Mike Hill, Hongchao Pan, and Jill Boreham in the CTSU, Oxford, for assisting with the design, planning, organization, and conduct of the study.
Details for the CKB collaborative group are given in the Appendix of Online supplement.
Supplementary materials related to this article can be found online at
Multivariable adjusted hazard ratios (95% confidence intervals) of incident stroke associated with family history of stroke according to stroke types and gender
Stratification analyses on associations between family history of stroke and incident stroke
Interaction analyses between family history of stroke and smoking status. (A) Results for total stroke; (B) results for hemorrhagic stroke; (C) results for ischemic stroke. Total stroke includes hemorrhagic stroke, ischemic stroke and stroke of unknown type. HRs and 95% CIs are adjusted for age, sex, marital status, education, residential area, alcohol consumption, physical activity, BMI, history of hypertension, history of diabetes and siblings. Round dots represent the HRs, and horizontal lines represent the corresponding 95% CIs. Current refers to current regular smoker. Not current refers to not current regular smoker. FHS(-) refers to without FHS. FHS(+) refers to with FHS. The dashed lines represent participants who are not current smokers and without FHS as reference groups. FHS, family history of stroke; HR, hazard ratio; CI, confidence interval; BMI, body mass index.
Hazard ratios (HRs) (95% confidence intervals [CIs]) of incident stroke associated with each type of family history of stroke according to stroke types. Total stroke includes hemorrhagic stroke, ischemic stroke and stroke of unknown type. HRs and 95% CIs of Model 1 are adjusted for age and sex; HRs and 95% CIs of Model 2 are adjusted for age, sex, marital status, education, residential area, smoking status, alcohol consumption, physical activity, body mass index, history of hypertension, history of diabetes and siblings. Round dots represent the HRs, and horizontal lines represent the corresponding 95% CIs.
Hazard ratios (HRs) (95% confidence intervals [CIs]) of incident stroke associated with family history of stroke according to age groups. (A) Results for total stroke; (B) results for hemorrhagic stroke; (C) results for ischemic stroke. Total stroke includes hemorrhagic stroke, ischemic stroke and stroke of unknown type. HRs and 95% CIs are adjusted for sex, marital status, education, residential area, smoking status, alcohol consumption, physical activity, body mass index, history of hypertension, history of diabetes and siblings. Round dots represent the HRs, and horizontal lines represent the corresponding 95% CIs.
Baseline characteristics of the study population according to family history of stroke
Characteristic | All subjects | Family history of stroke |
||
---|---|---|---|---|
No | Yes | |||
No. of participants | 473,849 (100.0) | 387,864 (81.9) | 85,985 (18.1) | |
Age (yr) | 50.8±10.5 | 50.8±10.7 | 51.1±9.7 | <0.001 |
Male | 192,834 (40.7) | 157,379 (40.6) | 35,455 (41.2) | <0.001 |
Rural area | 269,040 (56.8) | 223,874 (57.7) | 45,166 (52.5) | <0.001 |
Currently married | 431,697 (91.1) | 353,006 (91.0) | 78,691 (91.5) | <0.001 |
Middle school and above | 234,959 (49.6) | 186,132 (48.0) | 48,827 (56.8) | <0.001 |
Body mass index (kg/m2) | 23.6±3.35 | 23.5±3.34 | 24.0±3.36 | <0.001 |
Diabetes | 25,214 (5.3) | 19,934 (5.1) | 5,280 (6.1) | <0.001 |
Hypertension | 158,297 (33.4) | 123,809 (31.9) | 34,488 (40.1) | <0.001 |
Current regular smoker | 126,194 (26.6) | 102,991 (26.6) | 23,203 (27.0) | 0.010 |
Current regular drinker | 71,657 (15.1) | 57,758 (14.9) | 13,899 (16.2) | <0.001 |
Physical activity (MET h/day) | 21.7±13.9 | 21.8±13.9 | 21.0±13.9 | <0.001 |
Values are presented as mean ± standard deviation or n (%).
MET, metabolic equivalent of task.
HRs (95% CIs) of incident stroke according to types of stroke and family history status
Group | Family history status | No. of subjects | Incident strokes | Person-years | Incidence rate (per 1,000 person years) | Model 1 |
Model 2 |
||
---|---|---|---|---|---|---|---|---|---|
HR (95% CI) | HR (95% CI) | ||||||||
Total stroke |
No | 387,864 | 19,988 | 2,734,939 | 7.31 | 1.00 | 1.00 | ||
Yes | 85,985 | 6,407 | 603,322 | 10.62 | 1.50 (1.46–1.55) | 1.34 (1.31–1.38) | |||
1 member | 74,931 | 5,158 | 527,282 | 9.78 | 1.41 (1.37–1.46) | 1.28 (1.24–1.32) | |||
2 members | 9,796 | 1,044 | 67,602 | 15.44 | 1.98 (1.86–2.11) | 1.66 (1.56–1.77) | |||
≥3 members | 1,258 | 205 | 8,439 | 24.29 | 2.47 (2.15–2.84) | <0.001 | 1.93 (1.68–2.21) | <0.001 | |
Hemorrhagic stroke | |||||||||
No | 371,787 | 3,911 | 2,663,576 | 1.47 | 1.00 | 1.00 | |||
Yes | 80,635 | 1,057 | 579,429 | 1.82 | 1.28 (1.20–1.37) | 1.24 (1.16–1.33) | |||
1 member | 70,634 | 861 | 508,128 | 1.69 | 1.21 (1.13–1.31) | 1.18 (1.10–1.28) | |||
2 members | 8,916 | 164 | 63,617 | 2.58 | 1.64 (1.41–1.92) | 1.53 (1.31–1.79) | |||
≥3 members | 1,085 | 32 | 7,683 | 4.17 | 2.11 (1.49–2.99) | <0.001 | 1.89 (1.33–2.67) | <0.001 | |
Ischemic stroke | |||||||||
No | 383,225 | 15,349 | 2,716,424 | 5.65 | 1.00 | 1.00 | |||
Yes | 84,757 | 5,179 | 598,374 | 8.66 | 1.59 (1.54–1.64) | 1.39 (1.34–1.43) | |||
1 member | 73,930 | 4,157 | 523,235 | 7.94 | 1.48 (1.43–1.54) | 1.32 (1.27–1.36) | |||
2 members | 9,604 | 852 | 66,854 | 12.74 | 2.11 (1.97–2.26) | 1.72 (1.60–1.84) | |||
≥3 members | 1,223 | 170 | 8,285 | 20.52 | 2.69 (2.31–3.13) | <0.001 | 2.01 (1.73–2.34) | <0.001 |
HR, hazard ratio; CI, confidence interval.
Model 1: adjusted for age and sex.
Model 2: Model 1 plus adjustment for marital status, education, residential area, smoking status, alcohol consumption, physical activity, body mass index, history of hypertension, history of diabetes and siblings.
Including hemorrhagic stroke, ischemic stroke and stroke of unknown type.
Details for members of the China Kadoorie Biobank collaborative group: International Steering Committee: Junshi Chen, Zhengming Chen (PI), Rory Collins, Liming Li (PI), Richard Peto. International Co-ordinating Centre, Oxford: Daniel Avery, Derrick Bennett, Yumei Chang, Yiping Chen, Zhengming Chen, Robert Clarke, Huaidong Du, Xuejuan Fan, Simon Gilbert, Alex Hacker, Michael Holmes, Andri Iona, Christiana Kartsonaki, Rene Kerosi, Ling Kong, Om Kurmi, Garry Lancaster, Sarah Lewington, John McDonnell, Winnie Mei, Iona Millwood, Qunhua Nie, Jayakrishnan Radhakrishnan, Sajjad Rafiq, Paul Ryder, Sam Sansome, Dan Schmidt, Paul Sherliker, Rajani Sohoni, Iain Turnbull, Robin Walters, Jenny Wang, Lin Wang, Ling Yang, Xiaoming Yang. National Co-ordinating Centre, Beijing: Zheng Bian, Ge Chen, Yu Guo, Bingyang Han, Can Hou, Jun Lv, Pei Pei, Shuzhen Qu, Yunlong Tan, Canqing Yu, Huiyan Zhou. 10 Regional Co-ordinating Centres: Qingdao CDC: Zengchang Pang, Ruqin Gao, Shaojie Wang, Yongmei Liu, Ranran Du, Yajing Zang, Liang Cheng, Xiaocao Tian, Hua Zhang. Licang CDC: Silu Lv, Junzheng Wang, Wei Hou. Heilongjiang Provincial CDC: Jiyuan Yin, Ge Jiang, Shumei Liu, Zhigang Pang, Xue Zhou. Nangang CDC: Liqiu Yang, Hui He, Bo Yu, Yanjie Li, Huaiyi Mu, Qinai Xu, Meiling Dou, Jiaojiao Ren. Hainan Provincial CDC: Jianwei Du, Shanqing Wang, Ximin Hu, Hongmei Wang, Jinyan Chen, Yan Fu, Zhenwang Fu, Xiaohuan Wang, Hua Dong. Meilan CDC: Min Weng, Xiangyang Zheng, Yijun Li, Huimei Li, Chenglong Li. Jiangsu Provincial CDC: Ming Wu, Jinyi Zhou, Ran Tao, Jie Yang. Suzhou CDC: Jie Shen, Yihe Hu, Yan Lu, Yan Gao, Liangcai Ma, Renxian Zhou, Aiyu Tang, Shuo Zhang, Jianrong Jin. Guangxi Provincial CDC: Zhenzhu Tang, Naying Chen, Ying Huang. Liuzhou CDC: Mingqiang Li, Jinhuai Meng, Rong Pan, Qilian Jiang, Jingxin Qing, Weiyuan Zhang, Yun Liu, Liuping Wei, Liyuan Zhou, Ningyu Chen, Jun Yang, Hairong Guan. Sichuan Provincial CDC: Xianping Wu, Ningmei Zhang, Xiaofang Chen, Xuefeng Tang. Pengzhou CDC: Guojin Luo, Jianguo Li, Xiaofang Chen, Jian Wang, Jiaqiu Liu, Qiang Sun. Gansu Provincial CDC: Pengfei Ge, Xiaolan Ren, Caixia Dong. Maiji CDC: Hui Zhang, Enke Mao, Xiaoping Wang, Tao Wang. Henan Provincial CDC: Guohua Liu, Baoyu Zhu, Gang Zhou, Shixian Feng, Liang Chang, Lei Fan. Huixian CDC: Yulian Gao, Tianyou He, Li Jiang, Huarong Sun, Pan He, Chen Hu, Qiannan Lv, Xukui Zhang. Zhejiang Provincial CDC: Min Yu, Ruying Hu, Le Fang, Hao Wang. Tongxiang CDC: Yijian Qian, Chunmei Wang, Kaixue Xie, Lingli Chen, Yaxing Pan, Dongxia Pan. Hunan Provincial CDC: Yuelong Huang, Biyun Chen, Donghui Jin, Huilin Liu, Zhongxi Fu, Qiaohua Xu. Liuyang CDC: Xin Xu, Youping Xiong, Weifang Jia, Xianzhi Li, Libo Zhang, Zhe Qiu.