Gender Specificity of Spousal Concordance in the Development of Chronic Disease Among Middle-Aged and Older Chinese Couples:  A Prospective Dyadic Analysis

DOI: https://doi.org/10.21203/rs.3.rs-77516/v1

Abstract

Background

This study aimed to explore the gender specificity of spousal concordance in the development of chronic diseases among middle-aged and older Chinese couples.

Methods

Data of 3420 couples (husbands: mean age, 57.5 years, SD = 8.5; wives: mean age, 55.6 years, SD = 8.0) were obtained from the China Health and Retirement Longitudinal Study (CHARLS). Multivariate logistic regression was used to analyze the incidence of chronic disease development over 4 years, conditional on the spousal baseline chronic disease status; and stepwise adjusting for the couples’ sociodemographic characteristics (i.e. age, education, retirement status and household income), and their individual lifestyle (i.e. smoking, drinking, exercise, social participation and (pre-)obesity) all measured at baseline.

Results

The incidence of chronic diseases after 4 years of follow-up was 34.5% in the husbands (727/2110) and 37.2% in the wives (882/2371). Taking the couples’ baseline sociodemographic and lifestyle covariates into account, husbands whose wife had a chronic disease at baseline showed an increased risk of developing a chronic disease over 4 years (ORadjusted=1.37, 95% CI:1.14,1.63), but this risk was not statistically-significant for wives (ORadjusted=1.16, 95%CI:0.97,1.40).

Conclusions

Our study identified gender specificity of spousal concordance in the development of chronic diseases among middle-aged and older- Chinese couples. This finding may contribute to the design of couple-based intervention for disease prevention and management for community-dwelling older adults.

Background

China has the world’s largest number of older adults, estimated at 248 million in 2020 and projected to rise to 482 million by 2053 [1, 2]. In addition to the accelerated population ageing process, the burden of chronic diseases continues to grow. Chronic diseases are the leading causes of premature death [3] and impose a heavy burden on society and family. It is estimated that the number of middle-aged and older patients with chronic diseases will triple to 300 million by 2050 [4]. Furthermore, a 2016 nationwide survey of older Chinese adults recorded 4363 ‘empty-nest’ older couples (37.9% of the 11,511 older adults investigated) who relied mainly on each other for daily care [5].

Spousal concordance, that is, consistency in health status between a husband and a wife, has been well documented [6]. A range of cross-sectional studies on spousal concordance in chronic disease has been conducted worldwide, with evidence primarily of lifestyle-related chronic diseases, such as hypertension [7, 8], cardiovascular disease [9–11], cancer [12, 13] and type 2 diabetes [14, 15]. This spousal concordance in chronic disease may be explained by assortative mating and the shared resources hypothesis. Assortative mating suggests that individuals tend to choose a spouse with a similar demographic profile, lifestyle and life attitudes [16], whilst the shared resources hypothesis states that a couple’s shared living environment, economic resources [6, 15], lifestyles [17–19] and social networks [20] may lead to their convergence in health status.

In line with the proposed hypotheses, cultural differences in spousal concordance in chronic disease have been identified [21]. Couples’ relationships may be influenced by different cultures; for example, an individual-oriented culture emphasises independence and individual autonomy [22], whilst a collectivistic culture values connectedness and harmonious relationships [23]. Few Chinese studies have examined spousal concordance [17, 24, 25]. In line with the studies from other countries, these cross-sectional studies discovered spousal concordance in chronic disease. However, the study by Jurj et al. [17] was limited to women in Shanghai, and the information of their spouses was reported by the investigators instead of using paired data. Jichao Sun et al. [25] used community-based and national representative data, but the chronic disease was limited to diabetes. Both were cross-sectional studies that were unable to determine the chronological sequence of events and clear causal relationships. To sum up, Chinese studies focused only on cross-sectional study; rather, a cohort study with dyadic data would facilitate the understanding of concordance in the development of chronic disease among Chinese couples.

Moreover, gender differences in disease concordance within a couple have been suggested, given that the distinction of independency vs interdependency is shaped not only by culture but also by gendered roles, but evidence regarding the gender specificity of spousal concordance remains limited and inconclusive. Some studies found no gender specificity [10, 25, 26], whilst others reported that husbands were more likely to be affected by their female spouses with regard to obesity, physical health and well-being [27–29]; in contrast, some showed that wives were more likely to be affected by their husband with regard to depression and chronic diseases [21, 30–32]. To the best of our knowledge, the only prospective study in a Chinese cohort, which included 483 middle-aged and older adults from the Taiwan Longitudinal Study on Aging (TLSA; year: 2000–2006), showed that the effects of spousal health status on the personal development of a cardiovascular disease or metabolic syndrome were only observed in wives [31]. Therefore, the cohort studies on the gender specificity of spousal concordance have not yielded a consistent conclusion. Paired data were rarely used, less focus was placed on the development of chronic diseases, and studies with larger samples were not conducted among middle-aged and older Chinese couples.

This prospective cohort study aimed to investigate the gender specificity of spousal concordance in the development of chronic diseases in middle-aged and older Chinese couples. We hypothesised that 1) the development of chronic diseases would co-occur among these couples, such that the participants whose spouse had a chronic disease at baseline would experience an increased risk of chronic disease development during the follow-up period relative to those with a healthy spouse; and 2) the extent to which husbands’ and wives’ development of chronic disease would be affected by their sick partners would differ.

Methods

Study samples

Our study sample was derived from the China Health and Retirement Longitudinal Study (CHARLS 2011–2015), a nationally representative longitudinal study of community-dwelling older adults aged 45 years and above, with a follow-up interval of 2 years (Wave 1 [baseline, 2010–2011], Wave 2 [2012–2013] and Wave 3 [2014–2015]) [33]. Our sample comprised 3420 CHARLS couples that fulfilled the following criteria: 1) both spouses were included in the data; 2) both spouses were at least 45 years old at baseline; 3) both had complete data on chronic disease status at baseline (Wave 1, 2010–2011) and at the end of the 4-year follow-up (Wave 3, 2014–2015). Because our study’s aim was to explore spousal mutual influences on chronic disease development, couples in which both spouses had chronic diseases at baseline were excluded.

Measures

Chronic disease status. The respondents were asked whether they had received a diagnosis of any of the following chronic diseases in Wave 1 (2010–2011) and Wave 3 (2014–2015): high blood pressure, diabetes or high blood sugar, cancer and malignant tumour (excluding small skin cancer), chronic lung disease (e.g. emphysema and chronic bronchitis), cardiac disease (e.g. myocardial infarction, coronary heart disease, angina pectoris, heart failure and other heart problems), stroke, emotional or psychiatric problems, arthritis and dyslipidaemia [33]. Chronic disease status was assigned according to the answers to these questions, with ‘0’ referring to the absence of chronic disease and ‘1’ referring to the presence of at least one of these nine chronic diseases.

Chronic disease development. A binary variable was created to represent chronic disease development over 4 years (from Wave 1 to Wave 3). A change in the chronic disease status (‘1’) meant a change from no chronic disease to at least one studied chronic disease, whilst unchanged chronic disease status (‘0’) included the absence or presence of chronic disease at both Waves.

Covariates. Sociodemographic covariates at baseline (Wave 1) included age (in years; centred at 56.55 years), gender (men = 0; women = 1), education (lower secondary education = 0; upper secondary education = 1), retirement status (in-service = 0; retired = 1) and household total income (in thousand RMB).

Lifestyle. Key lifestyles were selected according to the spousal health concordance literature [6, 15, 18, 20] and included smoking, drinking, exercise, social participation and (pre-)obesity at baseline (Wave 1). Smoking was identified via a ‘yes’ response to the question ‘still chewed tobacco, smoked a pipe, smoked self-rolled cigarettes or smoked cigarettes/cigars?’ (no = 0; yes = 1). Drinking was identified via a ‘yes’ response to the question ‘Did you drink any alcoholic beverages, such as beer, wine or liquor in the past year?’ (no = 0; yes = 1). Exercise was identified via a ‘yes’ response to the question ‘During a usual week, did you do any moderate or vigorous activities for at least 10 minutes continuously? (moderate physical activities [e.g. bicycling and carrying light loads] or vigorous physical activities [e.g. heavy lifting, digging, ploughing, aerobics and fast bicycling]) (no = 0; yes = 1).’ Social participation was identified via a ‘yes’ response to the question ‘Have you done any of these activities in the last month? Interacted with friends; played mah-jong, chess or cards; or went to community club and so on’ (no = 0; yes = 1). Furthermore, (pre-)obesity [34] was classified by body mass index (BMI; less than 25 = 0; more than 25 = 1), which to some extent reflected diet behaviours [35]. The participants’ BMI was calculated as the mean of three measures of body weight in kilograms divided by the mean of height in meters squared (kg/m2) by a trained staff member using a health meter (Omron HN-286) and a stadiometer (SecaTM 213).

Statistical Methods

We used McNemar’s chi-square test and paired-sample t-test to examine the differences between spouses and a Kappa test to examine the associations between husbands and wives. The strength of the Kappa coefficients is interpreted in the following manner: 0.01 to 0.20 is slight; 0.21 to 0.40 is fair; 0.41 to 0.60 is moderate; 0.61 to 0.80 is substantial; and 0.81 to 1.00 is almost perfect. Pearson’s chi-square test (for two independent samples) was used to test the difference in the development of chronic disease between husbands and wives and to test the differences in the development of chronic disease between spouses with and without chronic diseases at baseline among husbands and wives.

The association between spousal chronic disease status at baseline and personal development of chronic disease over 4 years was estimated with logistic regression models for husbands and wives separately. In addition, participants who had a chronic disease at baseline were excluded from the logistic regression analysis, whereby 2110 couples and 2371 couples were included in the logistic regression among wives and husbands, respectively (Fig. 1). Four adjustment models were developed: Model 1 adjusted the ages of both spouses; Model 2 further adjusted other sociodemographic covariates (education level, retirement status and household income) of both spouses at baseline; in Model 3, personal lifestyles (smoking, drinking, social participation, exercise and (pre-)obesity [BMI > 25]) at baseline were adjusted; and in Model 4, we further adjusted for spousal lifestyle (smoking, drinking, social participation, exercise and (pre-)obesity [BMI > 25]) at baseline.

We used Stata MP 14.0 (College Station, TX, USA, 2014) to perform all analyses, with the significance level set as α = 0.05.

Results

Baseline characteristics of participants

A total of 5793 couples met the three inclusion criteria and were selected as the subjects of this study, but 2373 couples were excluded because both spouses had received a diagnosis of a chronic disease at baseline. Finally, 3420 couples were included in the analysis. Among the 3420 couples at baseline (Fig. 1), both spouses were free of chronic disease in 31.02% couples, only the husband had a diagnosed chronic disease in 30.67% couples, and only the wife had a diagnosed chronic disease in 38.30% couples.

As shown in Table 1, among the 3420 couples, the husbands were older, better educated and less likely to be retired than their wives (all P < 0.001). Baseline lifestyles also showed that the husbands were more likely to smoke, drink alcohol and exercise, but they were less likely to have (pre-) obesity than their wives (all P < 0.001). The Kappa coefficient showed only fair agreement within couples on social participation (Kappa coefficient = 0.36; P < 0.001), but slight agreement on smoking, drinking, exercise and (pre-) obesity. At baseline, 30.67% of husbands and 38.30% of wives reported at least one chronic disease.

Chronic disease development

After 4 years of follow-up, among those who had no chronic disease at baseline, the incidence of chronic disease was 34.46% in husbands (727/2110) and 37.20% in wives (882/2371; P = 0.056) (Table 1).

Gender specificity of spousal concordance in chronic disease development

The husbands whose wife had a chronic disease at baseline reported a higher incidence of chronic disease at Wave 3 than those whose wife did not have a chronic disease at baseline (37.40% vs. 30.82%; P < 0.001, data not tabulated). A similar finding was shown in women (39.37% vs. 35.05%; P = 0.041).

In the multivariate analyses for husbands (Table 2), after adjustment for different sets of covariates, the association between spousal (wives’) baseline chronic disease status and the husbands’ development of chronic disease remained significant (ORadjusted range, 1.32 to 1.37; P < 0.01).

In similar analyses for wives (Table 2), after adjustment for different sets of covariates, no significant association was discovered between spousal (husbands’) baseline chronic disease status and the wives’ development of chronic disease (ORadjusted range, 1.14 to 1.16; P > 0.05).

Discussion

Based on 3420 pairs of middle-aged and older Chinese couples of a national representative ageing cohort, we found that almost one third of study participants developed at least one chronic disease over 4 years of follow-up. Moreover. After adjustment for baseline confounders, husbands whose wives had a chronic disease at baseline had an increased risk of chronic disease development over time, but this risk was not significant for wives conversely.

Our study contributes to the literature of spousal health concordance by investigating the development of chronic disease over four years conditional on spousal chronic diseases, stratified by gender and adjusted for covariates of both couples. Few studies previously had investigated spousal concordance in chronic disease development, which mainly focused on concurrent association of health status [6, 10, 36] and health behaviors [6, 37, 38]. Our finding of the spouse-dependent onset of chronic diseases was consistent with recent studies about the spousal concordance in obesity development [28], changes in biomarker and subjective well-being [31], and mental health and self-reported health trajectories [29]. We extended the evidence in a Chinese community-based setting, with lifestyle data directly collected from both couples, and health status defined by multiple chronic disease status that were more common in older adults [39].

In view of the inconsistent findings on gender variation [29, 30], we further advanced the literature by investigating spousal health concordance gender-specifically. In general, previous studies of married couples have shown that the health benefits of marriage and the health detriments of marital dissolution differ by gender [6, 40, 41]. Our study showed that the influence of the spouse’s health on the other was only evident in husbands but not wives. This finding was in line with previous findings that husbands but not wives experienced declines in self-reported health after their spouse’s onset of chronic diseases [29], and husbands’ but not wives’ obesity development was associated with their spouses’ diabetes status [28]. Yet our finding was different from other findings that wives were more likely to be impacted by their spouses’ chronic status psychologically and physically compared to husbands [30, 32].

Possible reasons for our gender-specific finding may result from as follows. Wives paly a predominant role of caregiver in the family under greater socialisation factors [42], which is practically true under the traditional Chinese gendered social role, namely ‘breadwinning men and homemaking women’ [39, 43]. Husbands may be more dependent on their spouses regarding lifestyles and health management, such that husbands whose spouse with chronic diseases may suffer more chronic disease risk than their female counterparts. Moreover, as suggested by literature men tend to maintain intimate relationships with fewer people and receive social support primarily from their spouses [44, 45], while women are more likely to have broader social support other than that of their spouses [44, 46]. Chinese retired women are more socially-engaged than their male counterparts, actively participating in social- and physical- group activities, such as square-dancing [47]. While wives’ lifestyle can be also influenced by their peers [47], their husbands’ health status may be mostly influenced by their wives’ lifestyle and lifestyle-related chronic disease status [48, 49].

These gender-specific association of chronic disease development was largely independent of sociodemographic and lifestyle factors included. Possible reasons for these non-significant adjustments may result from limited variations in our participants’ retirement status, education and exercise levels that may be underpowered to detect a statistically-significant adjustment for the given sample size. Moreover, variations in lifestyles were further reduced as we only included baseline measures, which were likely to change as participants aged and be influenced by the older couples’ health status [50].

Given the greater frequency of chronic diseases and increased dependency that occur in later life [51], our finding shows that for chronic disease prevention in China, spousal concordance in the development of chronic disease could inform prevention advice that shifts the focus from optimising prevention efforts for the individual patient alone to optimising couple-based interventions. Moreover, spousal concordance could also be used for earlier detection of chronic diseases to make people recognise and respond to health problems earlier and be more willing to undergo treatment [15, 52]. Our finding of gender specificity also indicates that the diagnosis of a chronic disease in one spouse may warrant increased surveillance in his/her partner, because a husband whose wife has a chronic disease may obtain benefit from such increased surveillance.

With a prospective dyadic design stratified by gender, our study explored gender specificity in the spousal concordance of chronic disease development over 4 years based on a population-representative sample of middle-aged and older Chinese couples. Several limitations warrant notice. First, our study used baseline lifestyles to obtain their clear temporal relationship with the incidence of chronic disease during the follow-up period, which overlooked lifestyle changes over time. Further studies are needed to better understand the dynamics between lifestyle and chronic disease development with age. Second, we defined chronic disease status in a purely qualitative manner (i.e. at least one of nine chronic diseases) rather than by quantity or specified disease. Metabolic and cardiovascular diseases may be more susceptible to influence from lifestyle than other chronic diseases, and multiple chronic diseases and single chronic diseases should be discussed separately. Thus, further investigation of specified disease type and quantity is needed. In addition, our study primarily used self-reported measures and lacked an eating behaviour measure. To reduce information bias and recall bias, eating behaviour measures, objective measures such as biomarkers, and physician verification of chronic disease status would improve the accuracy of the findings.

Conclusions

This study revealed gender-specific patterns of spousal concordance in the development of chronic disease among community-dwelling middle-aged and older Chinese couples and demonstrated that husbands whose wife had a chronic disease at baseline had an increased risk of developing a chronic disease over the next 4 years, but this risk was not significant for wives. Our finding may inform the design of couple-based chronic disease management for older adults to better serve the health needs of the ageing population, whereby the health status and risk factors of both spouses would be jointly examined. Our findings suggest that women should be supported and men motivated for chronic disease surveillance if their spouse has a chronic disease.

Abbreviations

CHARLS: China Health and Retirement Longitudinal Study; CI, confidence interval; OR, odds ratio; SD, standard deviation.

Declarations

Ethics approval and consent to participate

The analysis is based on CHARLS data open to researchers. The original CHARLS was a survey approved by the Ethics Review Committee of Peking University, and all participants gave written informed consent at the time of participation.

Consent for publication

Not applicable

Availability of data and materials

The datasets analysed in this study are available from The China Health and Retirement Longitudinal Study (CHARLS 2011–2015) repository, and the searchable website www.g2aging.org can be used to access the CHARLS 2011–2015 data.

Competing interests

The authors declare that they have no competing interests.

Funding

This work is supported by the National Natural Science Foundation of China (#71804201) and the Natural Science Foundation of Guangdong Province (#2018A0303130046). The funders have no role in the design of the study; in the collection, analysis and interpretation of data; or in the writing of the manuscript.

Authors’ contributions

JG and JL conceived the research questions. JZ and JL conducted the statistical analysis and drafted the manuscript. JL, JG and JZX revised the manuscript and gave scientific comments. JZ finalized the manuscript and was a major contributor in writing the manuscript. All authors read and approved the final manuscript.

Acknowledgements

We thank all the participants who contributed to The China Health and Retirement Longitudinal Study (CHARLS 2011–2015), including Peking University, the National Natural Science Foundation of China, the Behavioural and Social Research Division of the National Institute on Aging, and the World Bank.

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Tables

Table 1.
Baseline characteristics and chronic disease status at Wave 1 and Wave 3 by gender (3420 couples)
 
Husbands
n = 3420
Wives
n = 3420
P (for difference)
Kappa
P (for Kappa)
%
%
Sociodemographic characteristics at baseline
        
Age, year [Mean (SD)]
57.54 (8.54)
55.61 (8.01)
< 0.001
0.12
< 0.001
Education level, Upper secondary
17.31
8.89
< 0.001
0.28
< 0.001
Retired, yes
16.20
24.50
< 0.001
0.39
< 0.001
Household income, thousand [Mean (SD)]
33.84 (69.17)
-
-
-
Lifestyles at baseline
          
Smoking, yes
60.29
5.67
< 0.001
0.01
0.047
Drinking, yes
59.94
11.81
< 0.001
0.06
< 0.001
Social participation, yes
48.07
46.14
0.05
0.36
< 0.001
Exercise, yes
77.08
73.98
< 0.001
0.19
< 0.001
(Pre-)obesity (BMI > 25), yes
23.07
33.51
< 0.001
0.07
< 0.001
Chronic disease status #
          
Wave 1 (baseline, 2010–2011), yes
30.67
38.30
< 0.001
-
-
Wave 3 (2014–2015), yes
51.55
58.68
< 0.001
-
-
Chronic disease development (Wave 1 to Wave 3) ##
        
Changed chronic disease condition, yes
34.46
37.20
0.056a
-
-
SD: Standard Deviation. a: P value of chi-square test of two independent groups.
#: Chronic disease status: ‘yes’ refers to the presence of at least one of nine chronic diseases: high blood pressure, diabetes or high blood sugar, all kinds of cancer and malignant tumour, chronic lung diseases/heart disease, stroke, mental illness, arthritis and dyslipidaemia.
##: Chronic disease development: Among those who had a negative chronic disease status at baseline (2110 husbands, 2371 wives). ‘yes’ indicates that the chronic disease status had changed from disease-free to the presence of at least one of nine chronic diseases over 4 years (from Wave 1 to Wave 3).

 

Table 2.
Influence of spousal baseline chronic disease status on one’s chronic disease development over 4 years.
 
Chronic disease development over 4 years (yes)
Model 1
Model 2
Model 3
Model 4
ORa (95% CI)
ORa (95% CI)
ORa (95% CI)
ORa (95% CI)
For husbands (n = 2371)
        
Spousal baseline chronic disease status, yes
1.32 (1.11,1.58)**
1.33 (1.12,1.59)***
1.33 (1.12,1.59)***
1.37 (1.14,1.63)***
For wives (n = 2110)
        
Spousal baseline chronic disease status, yes
1.14 (0.96,1.37)
1.16 (0.96,1.39)
1.15 (0.96,1.38)
1.16 (0.97,1.40)
Model 1: adjusted for age of both spouses.
Model 2: adjusted for age of both spouses + other sociodemographic covariates (education level, retirement status and household income) of both spouses.
Model 3: adjusted for sociodemographic covariates (age, education level, retirement status and household income) of both spouse’s + personal lifestyles (smoking, drinking, social participation, exercise and [pre-]obesity [BMI > 25]).
Model 4: adjusted for covariates in Model 3 (sociodemographic covariates of both spouse’s and personal lifestyles) + spousal lifestyles (smoking, drinking, social participation, exercise and [pre-]obesity [BMI > 25]).
***: P < 0.001; **: P < 0.01.