Abstract
We investigated the association between metabolic risk factors in one spouse with incident hypertension in the other. Study sample included 1528 men and 1649 women aged ≥20 years from the Tehran lipid and glucose study with information on body mass index (BMI), waist circumference (WC), hypertension, type 2 diabetes mellitus (DM), and dyslipidemia. The hazard ratio (HR) and 95% confidence interval (95% CI) were estimated for the association of spousal metabolic factors and incident hypertension among men and women separately. A total of 604 and 566 cases of incident hypertension were observed in men and women, respectively. Among men, spousal DM was associated with a 40% (CI: 1.07‐1.83) excess risk of hypertension after adjusting for the men's own and their spouse's risk factors including BMI, DM, smoking, and physical activity level. Among women, spousal DM was associated with more than two times (2.11, 1.69‐2.63) higher risk of hypertension. After further adjustment for the women's own and their spouse's risk factors, the association was attenuated and remained marginally significant (1.25, 0.99‐1.58; P value = .053). Having a spouse with DM increases an individual's risk of hypertension, which raises the possibility of using preexisting information of one partner to guide the screening of the other partner.
Keywords: diabetes, hypertension, metabolic, spousal
1. INTRODUCTION
Hypertension is a major global health challenge, affecting more than 1 billion people worldwide, and this is projected to increase in 1.56 billion by 2025.1, 2 Uncontrolled hypertension is currently an important contributor for heart disease, stroke, kidney failure, and premature mortality.3, 4 Globally, hypertension is responsible for 13% of premature deaths in developed and developing countries.3, 5 According to an Iranian national survey in 2011, 25.6% of adults, aged 25‐70 years, had hypertension.6 Also, the crude incidence rate of hypertension was 33.6 per 1000 person‐years in Iranian population, over a decade long follow‐up.7 A wide variety of genetic and environmental factors predispose individuals to hypertension; although, contribution of genetic factors has been shown to be small.8 According to available evidence, a number of lifestyle behaviors including, smoking, diabetes, being obese or overweight, high cholesterol, excess salt intake, and physical inactivity play a greater role in developing hypertension.9, 10 Therefore, early detection of individuals at high risk for hypertension and proper management of these modifiable risk factors is important for primary prevention of hypertension.9 One approach to investigate the contribution of environmental factors in disease development is study of cohabiting couples because such spouses usually are not genetically related but share a common living environment, pool resources, eat together, and share a social network.11, 12 A large number of epidemiological studies demonstrated significant positive spousal concordance for diabetes mellitus (DM),13, 14, 15, 16 and the majority of main coronary risk factors including diastolic blood pressure (DBP), triglycerides (TG), total and low‐density lipoprotein cholesterol (TC and LDL‐C), smoking, body mass index (BMI), and waist‐to‐hip ratio.17, 18 A case‐control study of couples aged >30 years showed that spouses of hypertensive patients had a twofold increased risk of hypertension beyond the effect of age, BMI, and DM.19 A meta‐analysis of eight observational studies, including one case‐control, and seven cross‐sectional studies found that spouses of individuals with hypertension had increased odds of having hypertension.12 Although a few studies have assessed cross‐sectional associations of hypertension with spousal risk factors, to our knowledge, no prospective study has investigated the relation between spousal risk factors with incident hypertension. Hence, we undertook the present study with the aim of studying this association in a large sample of Iranian couples over 18 years of follow‐up in the Tehran lipid and glucose study (TLGS) cohort.
2. METHODS
2.1. Study population
Tehran lipid and glucose study is a large population‐based cohort study of a representative sample of Tehranian population aged >3 years initially designed to investigate the risk factors and outcomes for non‐communicable disease.20 Details of the study has previously been published.21 In brief, participants in this cohort were enrolled during 1999‐2002 (phase 1) and 2002‐2005 (phase 2) and followed in next phases (phases 2‐6), each conducted 3 years apart with the last one in 2015‐2018. In the present study, we included 12 790 individuals aged ≥20 years (10 362 from phase 1 and 2428 from phase 2) and used the genealogy dataset to identify couples among these individuals. In the TLGS, this dataset was derived from households in which unit of the family included parents and at least one child; hence, a “dummy person” was added to replace missing parents.22 We excluded the couples who did not have any child until end of study (18 April 2018), those that had gotten married before the age of 18 years (child marriage), and the couples who did not participate simultaneously at the same phase, resulting a total of 2866 eligible couples. As all analyses were performed separately for husbands and wives (index individuals), we excluded “index individuals” with prevalent hypertension at baseline (643 men and 557 women), those with missing data on hypertension status at baseline (76 men and 41 women), missing data on other covariates (293 men and 235 women), and those with no follow‐up data after enrolment until the end of the study (326 men and 267 women). Consequently, a total of 3177 individuals (1528 men and 1649 women) remained in the study. Families structures and drown pedigrees were confirmed by genomic data from the Tehran Cardiometabolic Genetic Study (TCGS).22 This study was approved by the ethics committee of the Research Institute for Endocrine Sciences of Shahid Beheshti University of Medical Sciences, Tehran, Iran, and was conducted adhering to the tenets of the Helsinki Declaration. All participants provided written consent prior to any study procedures.
2.2. Data collection
Information on age, sex, marital status, smoking status, education level, and medical and drug history were obtained from a standard questionnaire. Anthropometric measurements of waist circumference (WC), body height, and weight were performed by trained staffs using standard procedures,21 and BMI was calculated as weight in kilograms divided by height in meters squared (kg/m2). Blood pressure was recorded in a sitting position in the right arm using a standard mercury sphygmomanometer. Two measurements were taken at the interval of 5 minutes each, and mean of two readings was taken for systolic and diastolic blood pressure (SBP and DBP). After an overnight fast, participants provided a morning blood sample in the laboratories of each participating center for measurement of TC, TG, high‐density lipoprotein cholesterol (HDL‐C), fasting plasma glucose (FPG), and 2‐hour post‐load plasma glucose (2 hour‐PLPG).21 Lipid Research Clinics Physical Activity Questionnaire was used to assess the physical activity level (PAL) in the first phase of the study. In the second phase, the Modifiable Activity Questionnaire was used to measure three forms of activities including leisure time, job, and household activities in the past year.23
2.3. Definition of terms
Education level was classified into three categories: <6, 6‐11, and ≥12 years of schooling. The highest reported level of educational attainment at the couple level was used instead of socioeconomic status (SES) for both spouses. Smoking status was classified as smoker (current smokers) vs nonsmoker (past or never smokers). A current smoker was a person who smokes cigarettes or uses other tobacco products daily or occasionally. BMI categories were defined as normal (<25 kg/m2), overweight (25‐29.9 kg/m2), and obese (≥30 kg/m2). Central adiposity was defined as WC ≥ 90 cm for both genders.24 Hypertension was defined as a SBP ≥ 140 mm Hg or a DBP ≥ 90 mm Hg or taking antihypertensive drugs,25 and DM was defined as FPG ≥ 7 mmol/L or 2 hour‐PLPG ≥ 11.1 mmol/L26 or using glucose‐lowering medications. Dyslipidemia was defined as TG ≥ 1.69 mmol/L or HDL‐C levels <1.04 mmol/L in men and <1.29 mmol/L in women or TC ≥ 5.2 mmol/L or using lipid lowering medications.27 Low physical activity was defined as doing exercise or labor < three times a week or achieving a score of ≤600 metabolic equivalent task (MET)‐minutes per week.28
2.4. Exposures and outcome
The exposures were spouse's metabolic risk factors at baseline including BMI, WC, hypertension, DM, and dyslipidemia (all the variables in the categorical forms). The outcome of interest was the first occurrence of hypertension in index individuals during the follow‐up period.
2.5. Statistical methods
Baseline characteristics were compared between husbands and wives using Student's t test and Chi‐square test, as appropriate. We determined the strength and direction of the association between the same continuous and categorical risk factors in the husbands and the wives using the Pearson's and Spearman's correlation test, respectively. Additionally, we compared baseline characteristics of respondents and non‐respondents among index men and women. Respondents were those who had complete data at baseline with at least one follow‐up data, and non‐respondents included individuals with missing data at baseline or without any follow‐up data. The hypertension incidence rate and 95% confidence interval (95% CI) were calculated per 1000 persons‐years.
We used the Cox proportional hazard regression to assess the association between spousal metabolic risk factors and incident hypertension in index individuals. Survival time was defined as the time between baseline and the event date (for incident cases) or the last follow‐up (for censored cases). The event date was defined as the mid‐time between the date of the follow‐up visit when the hypertension was diagnosed for the first time, and the most recent follow‐up visit prior to the diagnosis. Respondents were censored due to death from a cause other than hypertension, loss to follow‐up, or the end of the study without the event occurring.
Five nested adjusted Cox models were developed. Model 1 included only spousal risk factor (unadjusted model), and model 2 was further adjusted for SES. In model 3, we further adjusted for the index individual's age (continuous form) and respective spousal risk factor (categorical forms). Model 4 included all variables in model 3 plus index individual's BMI, PAL, smoking, and DM (all in categorical forms). Model 5 was further adjusted for spousal BMI, PAL, smoking, and DM (categorical forms). Models including spousal hypertension as exposure were adjusted for the index individual's SBP (continuous form). Proportional hazards assumptions in the Cox models were checked using statistical tests and graphical diagnostics based on the scaled Schoenfeld residuals and log‐log plots, indicating all proportionality assumptions were appropriate. Statistical analysis was performed with the R statistical software, version 3.4.0. All statistical tests were two‐sided, and statistical significance was set at P < .05.
3. RESULTS
Our study population included 3177 index individuals (1528 men and 1649 women), aged ≥20 years, with the mean (SD) ages of 44.9 (11.8) and 38.7 (10.6) years, respectively. Baseline characteristics of study sample are shown in Table 1. In general, both husbands and wives were predominantly of middle education and majority of them were overweight. Compared with index women, index men at baseline were older and had higher levels of WC, SBP, FPG, TG, and TC; but, lower levels of BMI and HDL‐C. Index men were also more likely to be smokers and inactive, compared with index women.
Table 1.
Baseline characteristics of individuals stratified by sex: Tehran Lipid and Glucose study (TLGS) (1999‐2016)
|
Men n = 1528 |
Women n = 1649 |
P value | |
|---|---|---|---|
| Continuous variables | |||
| Age (y) | 44.9 (11.8) | 38.7 (10.6) | <.001 |
| BMI (kg/m2) | 25.9 (3.7) | 27.2 (4.4) | <.001 |
| Waist circumference (cm) | 89.3 (10.3) | 86.5 (11.4) | <.001 |
| SBP (mm Hg) | 114.3 (11.1) | 111.3 (11.5) | <.001 |
| DBP (mm Hg) | 74.7 (8.0) | 74.3 (7.8) | .139 |
| FPG (mmol/L) | 5.4 (1.5) | 5.1 (1.4) | <.001 |
| 2 h‐PLPG (mmol/L) | 6.1 (3.1) | 6.3 (2.4) | .240 |
| TG (mmol/L) | 2.1 (1.4) | 1.6 (1.0) | <.001 |
| HDL‐C (mmol/L) | 0.9 (0.2) | 1.1 (0.2) | <.001 |
| TC (mmol/L) | 5.4 (1.1) | 5.2 (1.1) | .002 |
| Categorical variables | |||
| Education | |||
| <6 y of schooling | 362 (23.7) | 432 (26.2) | <.001 |
| 6‐11 y of schooling | 871 (57.1) | 1058 (64.2) | |
| ≥12 y of schooling | 293 (19.2) | 159 (9.6) | |
| Current smoker | 509 (33.3) | 65 (3.9) | <.001 |
| Low physically active | 1194 (78.1) | 1207 (73.2) | .001 |
| Dyslipidemia | 1356 (88.7) | 1455 (88.2) | .654 |
| Lipid lowering drug use | 24 (1.6) | 39 (2.4) | .109 |
| BMI category | |||
| Normal (<25 kg/m2) | 620 (40.6) | 532 (32.3) | <.001 |
| Overweight (<25‐29.9 kg/m2) | 684 (44.8) | 720 (43.7) | |
| Obese (≥30 kg/m2) | 224 (14.7) | 397 (24.1) | |
| Waist circumference >90 cm | 703 (46.0) | 570 (34.6) | <.001 |
Values are presented as mean (SD) and frequency (%) for continuous and categorical variables, respectively.
Abbreviations: 2 h‐PLPG, 2‐h post‐load plasma glucose; BMI, body mass index; DBP, diastolic blood pressure; FPG, fasting plasma glucose; HDL‐C, high‐density lipoprotein cholesterol; SBP, systolic blood pressure; SD, standard deviation; TC, total cholesterol; TG, triglyceride.
Baseline characteristics of respondent and non‐respondent individuals are shown in Table 2. Male respondents had higher levels of SBP and TC at baseline, compared with their non‐respondents counterparts. They had also higher probability of being a current smoker and inactive, compared with their non‐respondents counterparts.
Table 2.
The comparisons between respondents and non‐respondents: Tehran Lipid and Glucose study (TLGS) (1999‐2016)
| Women | Men | |||||
|---|---|---|---|---|---|---|
|
Non‐respondent n = 619 |
Respondent n = 1649 |
P value |
Non‐respondent n = 619 |
Respondent n = 1528 |
P value | |
| Continuous variables | ||||||
| Age (y) | 37.1 (10.4) | 38.7 (10.6) | .001 | 44.0 (12.0) | 44.9 (11.8) | .101 |
| BMI (kg/m2) | 27.6 (4.6) | 27.2 (4.4) | .083 | 25.5 (3.9) | 25.9 (3.7) | .059 |
| Waist circumference (cm) | 87.2 (11.6) | 86.5 (11.4) | .189 | 88.8 (10.8) | 89.3 (10.3) | .279 |
| SBP (mm Hg) | 109.5 (11.6) | 111.3 (11.5) | .001 | 112.9 (11.1) | 114.3 (11.1) | .009 |
| DBP (mm Hg) | 72.6 (8.2) | 74.3 (7.8) | <.001 | 74.2 (8.0) | 74.7 (8.0) | .188 |
| FPG (mmol/L) | 5.1 (1.4) | 5.1 (1.4) | .619 | 5.4 (1.7) | 5.4 (1.5) | .561 |
| 2 h‐PLPG (mmol/L) | 6.1 (1.9) | 6.3 (2.4) | .092 | 5.9 (2.5) | 6.1 (3.1) | .187 |
| TG (mmol/L) | 1.6 (1.1) | 1.6 (1.0) | .06 | 2.0 (1.4) | 2.1 (1.4) | .445 |
| HDL‐C (mmol/L) | 1.1 (0.2) | 1.1 (0.2) | .912 | 0.9 (0.2) | 0.9 (0.2) | .056 |
| TC (mmol/L) | 5.1 (1.1) | 5.2 (1.1) | .032 | 5.1 (1.0) | 5.4 (1.1) | <.001 |
| Categorical variables | ||||||
| Education | ||||||
| <6 y of schooling | 139 (22.5) | 432 (26.2) | .175 | 138 (22.3) | 364 (23.8) | .738 |
| 6‐11 y of schooling | 414 (66.9) | 1058 (64.2) | 362 (58.5) | 871 (57.0) | ||
| ≥12 y of schooling | 66 (10.7) | 159 (9.6) | 119 (19.2) | 293 (19.2) | ||
| Current smoker | 30 (4.8) | 65 (3.9) | .290 | 259 (41.8) | 509 (33.3) | <.001 |
| Low physically active | 457 (73.8) | 1207 (73.2) | .820 | 441 (71.2) | 1194 (78.1) | .001 |
| Dyslipidemia | 545 (88.1) | 1455 (88.2) | .941 | 538 (86.9) | 1356 (88.7) | .248 |
| Lipid lowering drug use | 20 (3.2) | 39 (2.4) | .240 | 6 (1.0) | 24 (1.6) | .318 |
| BMI category | ||||||
| Normal (<25 kg/m2) | 182 (29.4) | 532 (32.3) | .430 | 269 (43.5) | 620 (40.6) | .246 |
| Overweight (<25‐29.9 kg/m2) | 278 (45.0) | 720 (43.7) | 274 (44.3) | 684 (44.8) | ||
| Obese (≥30 kg/m2) | 159 (25.7) | 397 (24.1) | 76 (12.2) | 224 (14.7) | ||
| Waist circumference >90 cm | 229 (37.0) | 570 (34.6) | .318 | 282 (45.6) | 703 (46.0) | .457 |
Values are presented as mean (SD) and frequency (%) for continuous and categorical variables, respectively. Respondents: Eligible individuals with complete data at baseline with at least one follow‐up data. Non‐respondents: Eligible individuals with missing data at baseline or without any follow‐up data.
Abbreviations: 2 h‐PLPG, 2‐h post‐load plasma glucose; BMI, body mass index; DBP, diastolic blood pressure; FPG, fasting plasma glucose; HDL‐C, high‐density lipoprotein cholesterol; SBP, systolic blood pressure; SD, standard deviation; TC, total cholesterol; TG, triglyceride; WC, waist circumference.
Among women, respondents were younger and had higher levels of SBP, DBP, and TC.
Correlation coefficients (r) and levels of significance between the same risk factors in the couples were as follows: BMI 0.12; WC 0.17; SBP 0.32; DBP 0.15; FPG 0.13; 2 hour‐PLPG 0.16; HDL‐C 0.10; TC 0.15 (P < .001 for all); TG 0.06 (P < .01); smoking status 0.12 (P < .001); and PAL 0.06 (P < .05).
During the median (interquartile range) follow‐ups of 15.6 (13.5‐16.9) and 15.7 (14.3‐16.8) years, we found 604 and 566 new cases of hypertension in index men and women, respectively. The incidence rate (95% CI) per 1000 person‐years among index men and women was 34.6 (31.9‐37.5) and 27.8 (25.6‐30.2), respectively.
Among index men, the unadjusted analysis showed a strong association between spousal risk factors (overweight, obesity, central obesity, DM, hypertension, and smoking) and the risk of hypertension (Table 3, model 1). Most of these associations were not substantially altered following adjustment for SES, except for central obesity (model 2). After further adjustment for the index men's own age and respective spousal risk factor, only spousal DM was significantly associated with a 41% excess risk of hypertension hazard ratio (HR: 1.41, 95% CI: 1.08‐1.83) (model 3). When adjusted for additional confounders including index men's own BMI, PAL, DM, and smoking, spousal DM was associated with a 42% excess risk of hypertension incidence (1.42, 1.09‐1.85) (model 4). This association remained substantially unchanged after further adjustment for spousal BMI, smoking status, and PAL (1.40, 1.07‐1.83) (model 5).
Table 3.
The impact of spousal risk factors on hypertension incidence among index men (husbands, n = 1528): Tehran Lipid and Glucose study (TLGS) (1999‐2018)
| Spousal risk factors |
Model 1 HR (95% CI) |
Model 2 HR (95% CI) |
Model 3 HR (95% CI) |
Model 4 HR (95% CI) |
Model 5 HR (95% CI) |
|---|---|---|---|---|---|
| BMI category | |||||
| Normal weight (<25 kg/m2) | Reference | Reference | Reference | Reference | |
| Overweight (25‐29.9 kg/m2) | 1.43 (1.17‐1.75)* | 1.40 (1.15‐1.71)* | 1.11 (0.91‐1.37) | 1.11 (0.90‐1.36) | 1.09 (0.89‐1.34) |
| Obese (≥30 kg/m2) | 1.52 (1.22‐1.90)* | 1.33 (1.06‐1.67) * | 0.95 (0.75‐1.21) | 0.95 (0.75‐1.20) | 0.94 (0.75‐1.19) |
| Waist circumference ≥90 cm | 1.33 (1.13‐1.56)* | 1.17 (0.98‐1.38) | 0.93 (0.78‐1.11) | 0.90 (0.75‐1.07) | 0.86 (0.69‐1.07) |
| Hypertension | 1.60 (1.31‐1.95)* | 1.41 (1.15‐1.73)* | 1.04 (0.84‐1.28) | 1.03 (0.83‐1.28) | 1.02 (0.82‐1.27) |
| Dyslipidemia | 1.07 (0.82‐1.39) | 0.99 (0.76‐1.30) | 0.82 (0.63‐1.08) | 0.84 (0.64‐1.11) | 0.82 (0.62‐1.08) |
| Type 2 diabetes | 2.04 (1.59‐2.62)* | 1.75 (1.36‐2.27)* | 1.41 (1.08‐1.83)* | 1.42 (1.09‐1.85)* | 1.40 (1.07‐1.83)* |
Model 1: Unadjusted; including only spousal risk factor. Model 2: Included model 1 + SES. Model 3: Included model 2 + index individual's age + index individual's own value of the respective spousal risk factor. Model 4: Adjusted for model 3 + all risk factors in index individual including BMI, PAL, smoking, and type 2 diabetes. Model 5: Adjusted for model 4 + all spousal risk factors including BMI, PAL, smoking, and type 2 diabetes.
Abbreviations: BMI, body mass index; CI, confidence interval; HR, hazard ratio; PAL, physical activity level; SES, socioeconomic status.
P < .05.
Among index women, spousal DM and hypertension were significantly associated with increased risk for hypertension (Table 4, model 1). The increased risk for hypertension remained significant only for spousal DM after further adjustments for SES and woman's own value of the age and DM (1.33, 1.06‐1.67) (model 3). After further adjustment for women's BMI, PAL, DM, and smoking, the association was attenuated and remained marginally significant (1.23, 0.98‐1.55; P = .066) (model 4). Finally, in the fully adjusted model, spousal DM was associated with a 25% increased risk for hypertension in women (1.25, 0.99‐1.58; P = .053) (model 5).
Table 4.
The impact of spousal risk factors on hypertension incidence among index women (wives, n = 1649): Tehran Lipid and Glucose study (TLGS) (1999‐2018)
| Spousal risk factors |
Model 1 HR (95% CI) |
Model 2 HR (95% CI) |
Model 3 HR (95% CI) |
Model 4 HR (95% CI) |
Model 5 HR (95% CI) |
|---|---|---|---|---|---|
| BMI group (kg/m2) | |||||
| Normal weight (<25 kg/m2) | Reference | Reference | Reference | Reference | |
| Overweight (25‐29.9 kg/m2) | 1.13 (0.88‐0.94) | 1.16 (0.97‐1.39) | 1.08 (0.90‐1.30) | 1.09 (0.91‐1.31) | 1.08 (0.90‐1.30) |
| Obese (≥30 kg/m2) | 0.94 (0.73‐1.21) | 0.90 (0.69‐1.15) | 0.86 (0.66‐1.10) | 0.81 (0.63‐1.05) | 0.81 (0.62‐1.04) |
| Waist circumference ≥90 cm | 1.13 (0.96‐1.33) | 1.06 (0.901.26) | 0.96 (0.81‐1.13) | 0.93 (0.78‐1.10) | 0.90 (0.72‐1.13) |
| Hypertension | 1.66 (1.38‐2.00)* | 1.46 (1.21‐1.76)* | 0.96 (0.79‐1.17) | 0.98 (0.81‐1.19) | 0.98 (0.80‐1.20) |
| Dyslipidemia | 0.93 (0.71‐1.22) | 0.93 (0.71‐1.21) | 0.91 (0.69‐1.19) | 0.89 (0.68‐1.17) | 0.87 (0.66‐1.15) |
| Type 2 diabetes | 2.11 (1.69‐2.63)* | 1.81 (1.45‐2.27)* | 1.33 (1.06‐1.67)* | 1.23 (0.98‐1.55)** | 1.25 (0.99‐1.58)*** |
Model 1: Unadjusted; including only spousal risk factor. Model 2: Included model 1 + SES. Model 3: Included model 2 + index individual's age + index individual's own value of the respective spousal risk factor. Model 4: Adjusted for model 3 + all risk factors in index individual including BMI, PAL, smoking, and type 2 diabetes. Model 5: Adjusted for model 4 + all spousal risk factors including BMI, PAL, smoking, and type 2 diabetes.
Abbreviations: BMI, body mass index; CI, confidence interval; HR, hazard ratio; PAL, physical activity level; SES, socioeconomic status.
P < .05; **P = .066; ***P = .053.
4. DISCUSSION
In this prospective study of Iranian couples aged ≥20 years, we found that spousal DM was associated with increased risk of hypertension among both sexes independent of their own and their spouse's risk factors; however, the association was stronger in men compared with women. We found no statistically significant association between spousal BMI status, central obesity, hypertension, or dyslipidemia and risk for hypertension among both sexes.
To our knowledge, this is the first study in which the association between spousal metabolic risk factors and hypertension incidence has been prospectively investigated in a relatively large cohort study.
There is a growing literature investigating how couples influence each other's mental and physical health trajectories.11, 29 Two main theories have been suggested to explain spousal concordance: Assortative mating refers to the idea that people typically choose mates who are similar to them on various characteristics such as demographics, attitudes, and life style factors, including diet, physical activity, smoking, and alcohol consumption.15, 30, 31 Another theory is referred to as the shared resource,31 which speculates that when people marry, they typically have the same environment, pool resources, eat together, and share a social network. This shared environment contributes to behavioral convergence and shared health risks.11, 31
There is a large amount of data available on spousal concordance for important metabolic risk factors. A meta‐analysis of 71 observational studies including more than 100 000 couples found a significant positive within‐pair correlations for smoking, BMI, DBP, TG, TC, LDL‐C, weight, and waist/hip ratio.17 Consistent with prior literature, we found a positive correlation between couples for BMI, WC, SBP, DBP, FPG, 2 hour‐PLPG, HDL‐C, TC, TG, smoking, and PAL at baseline; but the correlations were generally weak and modest except for SBP (r = .32).
A recent meta‐analysis of eight cross‐sectional studies with a total number of 81 928 couples has shown that spouses of individuals with hypertension had 41% increased odds of having hypertension. This meta‐analysis found no statistically significant difference between studies with adjustment for BMI and in those without; as a results, the association was unlikely due to assortative mating, because, observed association did not strongly reduce when adjustment for BMI (a surrogate for assortative mating) was made.12
Although in our study we observed a positive correlation between couples for the baseline SBP, we did not find an elevated risk of hypertension incidence associated with spousal hypertension in both sexes.
Interestingly, in our study, only spousal DM was associated with an increased risk of hypertension in both sexes, after accounting for extensive adjustment for important risk factors. This association cannot be completely explained by assortative mating theory, because the risk of hypertension did not strongly reduce (especially for men) after adjusting for the index individual's own risk factors including BMI, PAL, DM, and smoking. Hence, our finding may be explained by the effect of cohabitation (second theory). Spouses typically have a common living environment and may expose each other to health risks via shared health behaviors.11 In the Atherosclerosis Risk in Communities (ARIC) Study with more than 25 years of follow‐up, the associations between BMI and change of obesity status among couples were investigated. The results of ARIC study showed that individuals whose spouses became obese had nearly two fold higher risk of becoming obese themselves.18 Also, in the Framingham Heart Study, a strong concordance was found between spouses in dietary patterns over time after adjustment for social contextual factors.32 Some dietary patterns high in refined starches, sugar, saturated, and trans fats have been shown to promote inflammation.33 Inflammation can have a detrimental effect on the vascular system and kidney function, which in turn can lead to the development of hypertension.34 Also, a number of prospective studies35, 36 have demonstrated an association between high levels of inflammation and the development of DM. Therefore, hypertension and DM share inflammation as a common risk factor. In our study, it is possible that spousal DM increase the risk of hypertension indirectly via resemblance of eating habits between spouses. Another factor that might explain why the spousal DM is a risk factor for incident hypertension is that spousal DM may be associated with stress and the quality of the marital interactions.37 The evidence suggests that being involved in the day‐to‐day management of a diabetic partner may serve as a chronic stressor.38, 39 It has been recognized that stress may contribute to repeated blood pressure elevations, which eventually may lead to hypertension.40 One cross‐sectional study showed that female caregivers had a higher risk of high blood pressure, compared with non‐caregivers.5 In this study, the association between husbands' DM and risk for hypertension in women was substantially attenuated and became marginally significant after further adjustment for the woman's own risk factors including BMI, PAL, and smoking. This indicates that the detrimental effect of spousal DM on hypertension risk in a woman is partly mediated by the woman's own risk factors. Therefore, women may be less affected by their husbands DM, by modifying their lifestyles.
In sum, current study found that the risk of incident hypertension among Iranian adults is associated with their spouse's DM. However, the association was stronger for men than for women. In other word, the wife's DM is a stronger risk factor for incident hypertension than the husband's is that. In fact, we have also observed a sex difference in our previous study in which spousal DM was associated with 23% higher risk of DM among women, but not among men.16
Our results have important implications for both public health practitioners and health care professionals. Current screening programmes and prevention strategies focus predominantly on individuals risk factors to identify people who are at high risk of developing hypertension. The observed association between spousal DM and hypertension incidence in this study raises the possibility of using preexisting information of one partner to guide the screening of the other partner.
Strengths of our study include a relatively large sample size and the long follow‐up period. However, our study has some limitations that must be considered when interpreting the results. First, we included all married couples who had at least one child to ensure included couples had been together for at least 1 year. In addition, due to adverse physiological and psychological impact of early marriage,41, 42 we excluded couples who married before 18 years; therefore, the findings may not be generalizable to all couples. Second, there was missing data on several covariates, and also, some study participants were lost to follow‐up. The statistically differences were observed between the respondent and the non‐respondent in some baseline characteristics. The respondent had higher values for baseline SBP, DBP, and age; therefore, the incidence of hypertension may be biased toward an overestimation. Third, since there was no information on some important confounders such as the built environment, access to care, diet quality,43 duration of marriage, and duration of the comorbidities of DM, hypertension, and dislipidemia, we could not examine their effect on our results. And last but not least, we included the baseline measures of risk factors in our analysis; these factors might have changed during the study period.
5. CONCLUSIONS
Having a spouse with DM increases the risk of developing hypertension among both men and women independent of their own and their spouse's risk factors. This suggests that a couples‐based approach may be beneficial for the early detection of hypertensive individuals and those at high risk of developing hypertension, especially in our country with high prevalence of prehypertension.44 Thus, when health care professionals encounter patients with diabetes, their attention should be given to the spouse of the patients as the individuals at high risk of developing hypertension.
CONFLICT OF INTEREST
None declared.
AUTHOR CONTRIBUTIONS
FA and FH designed the study. AR performed the statistical analysis and drafted the manuscript. KG was involved in data collection and preparation. FH and FA revised manuscript critically for important intellectual content. All authors read and approved the final manuscript.
ACKNOWLEDGMENTS
This study was conducted in the framework of the Tehran Lipid and Glucose Study (TLGS) and was supported by the Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences. We express our appreciation to TLGS participants and the research team members for their contribution to the study.
Ramezankhani A, Guity K, Azizi F, Hadaegh F. Spousal metabolic risk factors and incident hypertension: A longitudinal cohort study in Iran. J Clin Hypertens. 2020;22:95–102. 10.1111/jch.13783
Funding information
This study was supported by grant No. 121 from the National Research Council of the Islamic Republic of Iran.
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