Spousal Correlations for Lifestyle Factors and Selected Diseases in Chinese Couples

Jurj, Adriana L.; Wen, Wanqing; Li, Honglan; Zheng, Wei; Yang, Gong; Xiang, Yong‐Bing; Gao, Yu‐Tang; Shu, Xiao‐Ou

doi:10.1016/j.annepidem.2005.07.060

Cited by 88 publications

(135 citation statements)

References 31 publications

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“…Although the findings have been complex and varied across studies, mounting evidence indicates moderate to high similarity between spouses for a wide array of traits and characteristics, with little evidence of negative spouse correlations. This context is also the case for habits associated with lifestyle, such as alcohol consumption (Meyler et al 2007;Reynolds et al 2006), smoking habits (Di Castelnuovo et al 2008;Meyler et al 2007;Reynolds et al 2006), and exercise (Jurj et al 2006;Macken et al 2000;Price and Vandenberg 1980;Simonen et al 2002). Meta-analyses have suggested an overall moderate similarity for alcohol use (r = 0.36) (Reynolds et al 2006) and smoking (r = 0.23) (Di Castelnuovo et al 2008), though levels of similarity observed in different studies have ranged from negligible to high.…”

Section: Introductionmentioning

confidence: 88%

“…Meta-analyses have suggested an overall moderate similarity for alcohol use (r = 0.36) (Reynolds et al 2006) and smoking (r = 0.23) (Di Castelnuovo et al 2008), though levels of similarity observed in different studies have ranged from negligible to high. Studies exploring spouse similarity in exercise have generally reported correlations between 0.15 and 0.30 (Aarnio et al 1997;Perusse et al 1989;Price and Vandenberg 1980), with some studies reporting similarity higher than 0.40 (Jurj et al 2006;Willemsen et al 2003).…”

Section: Introductionmentioning

confidence: 96%

“…The theory of convergence is mainly evaluated by assessing spouse similarity in relation to marital duration or age (Di Castelnuovo et al 2008). Increasing similarity with marital duration has been observed for alcohol use (Price and Vandenberg 1980;Tambs and Moum 1992) and exercise (Falba and Sindelar 2008;Jurj et al 2006;Simonen et al 2002;Tambs and Moum 1992). Conversely, several studies have suggested divergence across marital duration (Jurj et al 2006;Knuiman et al 1996;Willemsen et al 2003), especially regarding smoking (Buss 1984;Jurj et al 2006;Price and Vandenberg 1980;Sutton 1980;Tambs and Moum 1992).…”

Section: Introductionmentioning

confidence: 96%

See 2 more Smart Citations

Non-Random Mating and Convergence Over Time for Alcohol Consumption, Smoking, and Exercise: The Nord-Trøndelag Health Study

et al. 2011

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Spouses tend to have similar lifestyles. We explored the degree to which spouse similarity in alcohol use, smoking, and physical exercise is caused by non-random mating or convergence. We used data collected for the Nord-Trøndelag Health Study from 1984 to 1986 and prospective registry information about when and with whom people entered marriage/cohabitation between 1970 and 2000. Our sample included 19,599 married/cohabitating couples and 1,551 future couples that were to marry/cohabitate in the 14-16 years following data collection. All couples were grouped according to the duration between data collection and entering into marriage/cohabitation. Age-adjusted polychoric spouse correlations were used as the dependent variables in non-linear segmented regression analysis; the independent variable was time. The results indicate that spouse concordance in lifestyle is due to both non-random mating and convergence. Non-random mating appeared to be strongest for smoking. Convergence in alcohol use and smoking was evident during the period prior to marriage/cohabitation, whereas convergence in exercise was evident throughout life. Reduced spouse similarity in smoking with relationship duration may reflect secular trends.

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Section: Introductionmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 96%

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Non-Random Mating and Convergence Over Time for Alcohol Consumption, Smoking, and Exercise: The Nord-Trøndelag Health Study

et al. 2011

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“…Another potential limitation of our study is that we did not collect information on exposures of the participants' partners that might influence female fertility, such as smoking. This situation, however, is unlikely to have major impact on our results since the potential bias would be limited by the association between the partner risk factor for anovulatory infertility, which is likely to be non-existent or small in the case of smoking status of the partner (Hull et al, 2000;Greenlee et al, 2003), and could be accounted for in part by adjusting for the same factor in women, as we did for smoking and other lifestyle characteristics, since spouses often share environmental exposures and lifestyle practices (Knuiman et al, 2005;Jurj et al, 2006).…”

Section: Discussionmentioning

confidence: 99%

A prospective study of dairy foods intake and anovulatory infertility

Chavarro¹,

et al. 2007

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BACKGROUND: Dairy foods and lactose may impair fertility by affecting ovulatory function. Yet, few studies have been conducted in humans and their results are inconsistent. We evaluated whether intake of dairy foods was associated with anovulatory infertility and whether this association differed according to fat content. METHODS: We prospectively followed 18 555 married, premenopausal women without a history of infertility who attempted a pregnancy or became pregnant during an 8-year period. Diet was assessed twice during the study using food-frequency questionnaires RESULTS: During follow-up, 438 women reported infertility due to an ovulatory disorder. The multivariate-adjusted relative risks (RR) [95% confidence interval (CI); P, trend] of anovulatory infertility comparing women consuming 2 servings per day to women consuming 1 serving per week was 1.85 (1.24-2.77; 0.002) for low-fat dairy foods. The RR (95% CI; P, trend) comparing women consuming 1 serving per day of high-fat dairy foods to those consuming 1 serving per week was 0.73 (0.52-1.01; 0.01). There was an inverse association between dairy fat intake and anovulatory infertility (P, trend 5 0.05). Intakes of lactose, calcium, phosphorus and vitamin D were unrelated to anovulatory infertility. CONCLUSIONS: High intake of low-fat dairy foods may increase the risk of anovulatory infertility whereas intake of high-fat dairy foods may decrease this risk. Further, lactose (the main carbohydrate in milk and dairy products) may not affect fertility within the usual range of intake levels in humans.

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“…As time goes by, their physical condition might become very similar to each other, and they become susceptible to similar diseases. 18 Because diet can alter gut microbiota, we analyzed the intestinal microbiome of eight people (four married couples) to observe changes in microbiota following a dietary intervention. We also determined how similar changes in individuals were to those in their partner.…”

Section: Introductionmentioning

confidence: 99%

Effect of Diet Change on Gut Microbiota: Observational Pilot Study of Four Urban Couples

Roh

Lee

Kim

et al. 2017

JOMES

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Background: Recent studies have focused on changes in gut microbiota following a dietary change. We identified how the distribution of gut microbiota changed when the dietary habits of young city dwellers improved using an intervention in which married couples shared the same dietary habits. Methods: Four married couples in their 30s with irregular eating habits and sedentary lifestyles were asked whether they had any uncomfortable symptoms. A nutritionist advised them to reduce their intake of processed meats, carbonated beverages, and late-night snacks. After a 6-week intervention, subjects were asked whether they observed any changes in their symptoms. Their stool samples were collected before and after the intervention and analyzed to determine whether the gut microbiota had changed. Results: After the dietary intervention, some subjective symptoms of the participants improved. Specifically, a subject who complained of frequent abdominal pain/diarrhea and one who complained of fatigue showed improvement in those symptoms. In addition, some subjects showed improvements in symptoms such as skin disease or constipation. Intestinal microorganisms between spouses who share the same dietary habits were found to be similar. Conclusion: Improvements in eating habits can change the distribution of gut microbiota and alleviate various uncomfortable medical symptoms. Within married couples, the distribution of gut microbiota became similar when the spouses shared the same dietary habits. These results suggest a possible correlation between familylevel changes in eating habits and the health of all family members.

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Spousal Correlations for Lifestyle Factors and Selected Diseases in Chinese Couples

Cited by 88 publications

References 31 publications

Non-Random Mating and Convergence Over Time for Alcohol Consumption, Smoking, and Exercise: The Nord-Trøndelag Health Study

Non-Random Mating and Convergence Over Time for Alcohol Consumption, Smoking, and Exercise: The Nord-Trøndelag Health Study

A prospective study of dairy foods intake and anovulatory infertility

Effect of Diet Change on Gut Microbiota: Observational Pilot Study of Four Urban Couples

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