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Relationship Satisfaction Reduces the Risk of Maternal Infectious Diseases in Pregnancy: The Norwegian Mother and Child Cohort Study

Relationship Satisfaction Reduces the Risk of Maternal Infectious Diseases in Pregnancy: The Norwegian Mother and Child Cohort Study

  • Roger Ekeberg Henriksen, 
  • Torbjørn Torsheim, 
  • Frode Thuen



The aims of this study were to explore the degree to which relationship satisfaction predicts the risk of infectious diseases during pregnancy and to examine whether relationship satisfaction moderates the association between stressful life events and the risk of infections.


This was a prospective study based on data from the Norwegian Mother and Child Cohort Study (MoBa) conducted by the Norwegian Institute of Public Health. Pregnant women (n = 67,244) completed questionnaires concerning relationship satisfaction and nine different categories of infectious diseases as well as socioeconomic characteristics and stressful life events. Associations between the predictor variables and the infectious diseases were assessed by logistic regression analyses. A multiple regression analysis was performed to assess a possible interaction of relationship satisfaction with stressful life events on the risk for infectious diseases.


After controlling for marital status, age, education, income, and stressful life events, high levels of relationship satisfaction at week 15 of gestation were found to predict a significantly lower risk for eight categories of infectious diseases at gestational weeks 17–30. No significant interaction effect was found between relationship satisfaction and stressful life events on the risk for infections.


This study examines to what degree partner satisfaction predicts the risk for infectious diseases in pregnancy. Maternal infectious disease during pregnancy has been recognized as an important risk factor for adverse foetal outcomes. Influenza during pregnancy is associated with an increased risk of preterm birth and low birth weight [1]. Urinary tract infection has been shown to increase the risk for preeclampsia [2]. Other possible consequences include the harmful impact on foetal development of the central nervous system. Evidence demonstrates that prenatal exposure to maternal influenza and genital infections are associated with an increased risk for schizophrenia [3,4]. Evidence also suggests that maternal infection and immune dysfunction may be associated with autism [4]. In addition to potentially harmful outcomes for mother and child, pregnant women are at an increased risk of hospitalization related to complications from an infectious disease compared with nonpregnant women [1]. Increased knowledge on factors that may reduce the prevalence of infectious diseases during pregnancy is of great importance for individuals as well as for society.

Relationships with family and friends are important factors in explaining inequalities in individuals’ health outcomes. Evidence clearly shows that individuals who perceive their social relationships as satisfying or supportive have better health and longer life expectancies than those who report less perceived support from others [57]. In adulthood, romantic relationships have been recognized to be particularly important in predicting health outcomes, and several studies have demonstrated the health benefits of being married compared to living alone [810]. Although couple relationships seem to be generally health promoting, research also shows that the advantage of being married depends on the quality of the relationship [1116]. This applies to a number of diseases and health conditions, including infectious diseases. For instance, Phillips and colleagues [17] demonstrated a positive relationship between a high degree of marital satisfaction and a higher antibody response to influenza vaccination in a sample of elderly individuals. Given that antibody response to vaccination is a reliable indicator of susceptibility to infectious diseases, the study suggests that individuals who score high on relationship satisfaction experience lower rates of infectious diseases.

Several possible mechanisms have been proposed to explain how the quality of romantic relationships may influence health, and a number of studies support that couple relationship quality influences health outcomes through both main effects and moderating effects [1820]. An adverse main effect may result from the tendency that individuals in low-quality relationships struggle with negative aspects related to spousal hostility and conflicts [21]. As with several other sources of psychosocial stress, marital distress has been linked to impairment of the immune system [22,23]. For instance, in a laboratory-based study, Kiecolt-Glaser and colleagues [23] found that married individuals who demonstrated hostile behaviour during a monitored discussion showed higher serum levels of pro-inflammatory cytokines, including interleukin-6 and tumour necrosis factor, compared to baseline levels. In addition to the direct effects mentioned above, relationship quality may moderate the adverse effects of other stressful experiences. It is well established that stressful life events predict alterations in the immune system and susceptibility to infectious diseases [2428]. Stressful experiences activate the hypothalamic–pituitary–adrenal–cortical system (HPA axis), which leads to the release of cortisol that, in turn, affects the immune system [29,30]. When exposed to a stressful event, support from the partner may reduce the stress-induced activation of the HPA axis [31]. A recent study found that partner support downregulated the effects of psychological distress on maternal cortisol secretion during pregnancy [32]. Interestingly, it seems that the level of partner-related moderation of stress-responses is a function of relationship quality. It has repeatedly been demonstrated that the stress-buffering effect of partner support tends to be stronger when the relationship quality is high [3133]. For example, an experiment conducted by Coan, Schaefer and Davidson [31] demonstrates how holding a partner’s hand during a stressful event influences activation in the neural systems supporting emotional and behavioural threat responses. 16 women were confronted with the threat of a mild electric shock while either holding their partners’ hands, holding a stranger’s hand, or alone. When exposed to the threat of shock without the support of handholding, the threat-related brain activity reached its highest level. When holding a stranger’s hand, the level of threat-related activity decreased as compared with receiving no support of handholding. While holding their partners’ hands, the participants showed the lowest levels of threat-related brain activity. Interestingly, the effects varied as a function of marital quality, with higher marital quality predicting less activation in the neuropsychological pathways associated with physiological stress responses.

In summary, the published studies suggest at least two sets of reasons why couple relationship quality may influence susceptibility to infections. First, individuals in the low-quality relationship group are likely to suffer from relational distress and the potentially harmful physiological stress responses that follow. Second, compared with individuals in high-quality relationships, those in low-quality relationships experience less efficient reduction of stress-induced activation in the HPA axis and therefore greater impairment of the immune system’s ability to fight infections. On the basis of the existing literature, we hypothesize that low levels of relationship satisfaction increases the risk for infectious diseases during pregnancy. We further hypothesize that the rate of stressful life events predicts the risk of infectious diseases and that the level of relationship satisfaction moderates this correlation.

Previous research on the general population has provided valuable information on the association between romantic relationship satisfaction and biomarkers that indicate susceptibility to infectious diseases [34]. Corresponding studies on the pregnant population are limited. Previous studies assessing the potentially health-protecting effects of relationship quality in pregnancy have focused on birth outcomes and maternal mental health [3538]. Therefore, the purpose of the present study is to extend the available knowledge regarding the effects of relationship satisfaction on manifested infectious diseases in pregnancy.

Materials and Methods

The Norwegian Mother and Child Cohort Study (MoBa) is a prospective population-based pregnancy cohort study conducted by the Norwegian Institute of Public Health [39]. In the period 1999–2008, all (except two) hospitals in Norway with more than 100 births per year invited pregnant women to participate in the study provided they could read Norwegian. They received a postal invitation three weeks before the ultrasound examination routinely offered to all pregnant women in Norway. Of the invited women, 40.6% consented to participate, and the cohort now includes 114,500 children, 95,200 mothers, and 75,200 fathers. Blood samples were obtained from both parents during pregnancy and from mothers and children (umbilical cord) at birth. Follow-up is conducted by questionnaires at regular intervals and by linkage to national health registries. Several sub-studies are conducting additional collections of data and biological materials. The current study is based on version 7 of the quality-assured data files released for research on 17 October 2012. A written informed consent was obtained from each MoBa participant upon recruitment. The study has obtained a licence from the Norwegian Data Inspectorate and was approved by The Regional Committee for Medical Research Ethics.


The present study includes married and cohabiting women participating in the MoBa study for the first time (n = 75,730). Thus, multi-time participating mothers were included with only their first participating pregnancy, and mothers living alone were excluded. Among those, 67,244 participants answered all questions of concern for the present study. This means that 8486 participants were excluded from the multivariate analyses due to missing values at one or more of the research variables. The participants had a mean age of 29.6 years (standard deviation [SD] 4.55); 52.1% were married, 47.9% were cohabiting, and the average duration of the couple relationships was 6.3 years (SD 4.33). The average level of education was higher for the sample than for the general population of women aged between 16–49 years (official statistics from 2008 in brackets): compulsory school 7.0% (28.1%), vocational school 26.7% (35.7%), three-year college 39.2% (29.8%), and university/higher education 21.9% (6.4%). The full sample has been compared with the general population of pregnant women in Norway and is described in more detail elsewhere [40].


Relationship satisfaction (RS) was measured during week 15 of the current pregnancy, using the full 10-items version of the Relationship Satisfaction Scale. The scale was developed for the MoBa and is based on core items used in previously developed measures of marital satisfaction and relationship quality [4143]. The scale has a six-step scoring format spanning from 1 ‘totally agree’ to 6 ‘don’t agree at all’. Examples of items are: ‘My partner and I have problems in our relationship’; ‘I am very happy in my relationship’; ‘My partner is generally very understanding’; and ‘I am satisfied with my relationship with my partner’. In the current sample the scale had a Cronbach’s alpha of 0.90. This scale has been used in previous studies [37,44]. In the logistic regression analyses, the scale was reversed and indexed to achieve a maximum score of 1 (low RS) and a minimum score of 0 (high RS).

Infectious diseases were measured during week 30 of the current pregnancy. The measure is based on a checklist covering nine different categories of infectious diseases: influenza, pneumonia/bronchitis, diarrhea/gastric flu, common cold, throat infection, sinusitis/ear infection, vaginal thrush, vaginal catarrh and bladder infection. The respondents were asked to mark whether they had (= 1) or had not (= 0) experienced the respective disease between weeks 17 and 30 of the current pregnancy. In order to examine the effect of relationship satisfaction and stressful life events on the total number of self-reported infections, a scale was constructed based on sum scores of the reported diseases.

Stressful Life Events (SLE) were measured during week 30 of the current pregnancy and consisted of 11 questions concerning different types of demanding experiences. Participants were asked to report whether they had experienced any of the listed situations during the preceding 12 months. Examples of questions are: ‘Have you had financial problems?’, ‘Have you had problems or conflict with your family, friends, or neighbours?’, ‘Has anyone close to you been seriously ill or injured?’, ‘Have you been involved in a serious accident, fire, or robbery?’ and ‘Have you lost someone close to you?’. The scoring format for each question was no (0) or yes (1). A scale was constructed based on sum scores reflecting the number of reported stressful life events, ranging from 0 to 8.

Control variables

Socioeconomic factors are, in general, known to predict physical health outcomes and were therefore included as control variables. These variables included age, marital status (married versus cohabiting), maternal income (scored from 1 = no income to 7 ≥ NOK 500,000 ≈ EUR 66,000), and educational level (six categories from public school to >4 years at university/college).

Statistical analyses

All statistical analyses were conducted using IBM SPSS, version 21. The associations between relationship satisfaction and infectious diseases were first tested by performance of separate bivariate logistic regression analyses for each of the nine different infectious diseases as the dependent variable and relationship satisfaction as the predictor variable. In order to assess the unique contribution of relationship satisfaction in the full model, nine additional multivariable logistic regression analyses were performed with the inclusion of the following independent control variables: age, marital status, education, income, and stressful life events. One logistic regression analysis was also conducted with all nine infections collapsed into one dichotomized variable (no infections versus one or more infections). To assess a possible interaction of relationship satisfaction with stressful life events on the number of self-reported infectious diseases, a hierarchical multiple regression analysis was performed by first entering the main predictor variables based on the continuous relationship satisfaction and stressful life events scores, with marital status, age, education, and income included as control variables. An interaction term based on the continuous relationship satisfaction and stressful life events scores was then added. In order to avoid collinearity between the main effects and the interaction term, both variables were centered on their means before multiplied together.


Descriptive analyses showed that the majority of the sample reported high levels of relationship satisfaction (M = 5.37, SD = 0.61). At least one infectious disease (M = 1.14, SD = 1.54) was experienced by 53.7% of the participants between week 17–30 of the current pregnancy. Stressful life events was experienced by 56.1% of the participants (1 SLE: 30.2%; 2 SLEs: 16.9%; 3 SLEs: 6.5%; 4 SLEs: 2.0%. Only 0.6% of the participants reported 5 or more SLEs). The mean number of reported stressful life events was 0.95 (SD = 1.07), ranging from 0 to 8. The results from the bivariate and multivariate logistic regression analyses and the prevalence of each disease are displayed in Table 1. The bivariate analyses showed a significant association between relationship satisfaction and eight of the infectious diseases, with odds ratios varying between 1.5 and 4.3 (95% CI). After adjusting for scores on stressful life events the odds ratios of the eight infections varied between 1.4 and 3.4, a decrease by an average of 0.38 (SD = 0.25) as compared with the unadjusted ORs. After adjusting for marital status, age, income, education, and stressful life events, the level of relationship satisfaction was still significantly associated with eight of the disease variables, with odds ratios varying between 1.6 and 3.3 (95% CI). When all nine groups of infections were collapsed into one dichotomized variable, the odds ratio was 2.1 (95% CI 1.86–2.40) in the bivariate analysis, 1.9 (95% CI 1.63–2.10) when adjusting for stressful life events, and 2.0 (95% CI 1.74–2.25) when adjusting for stressful life events, marital status, age, income, and education.

Table 1. Associations between relationship satisfactiona and self-reported infectious diseases.

A hierarchical multiple regression analysis was conducted that examined the interaction-effect of relationship satisfaction and stressful life events on the total number of self-reported infectious diseases. Model 1 included RS and SLE as the main predictor variables and age, income, education and marital status as control variables. The model explained 1.6% of the variance (adjusted R2 = .016, F(6,67237) = 182.494, p<.001). There was a significant positive association between the level of stressful life events and infectious diseases (unstandardized B = .125, standardized β = .087, p<.001) and a significant negative association between relationship satisfaction and infectious diseases (unstandardized B −.174, standardized β = −.069, p<.001). In Model 2 the interaction term RS × SLE was added. No statistically significant interaction effect was found between relationship satisfaction and stressful life events on the risk of infectious diseases (unstandardized B = −.015, standardized β = −.007, p= .066). By adding the interaction term, the R square did not change significantly (R2 change < 0.0001, F(1,67236) = 3.382, p = .066), and the explained variance of the model remained 1.6% (R2 = .016, F(7,67236) = 156.912, p<.001).


The present study examined the associations between relationship satisfaction and nine different groups of self-reported infectious diseases among married and cohabiting women in mid-pregnancy. The results from the logistic regression analyses showed that relationship satisfaction measured in week 15 of pregnancy is significantly associated with eight out of nine infectious diseases experienced between weeks 17–30 of pregnancy. The results persisted after controlling for scores on marital status, age, income, education, and stressful life events. Among the infections assessed in this study, only urinary bladder infection was not significantly associated with relationship satisfaction. All other groups of infectious diseases (influenza, pneumonia/bronchitis, diarrhea/gastric flu, common cold, throat infection, sinusitis/ear infection, vaginal thrush, and vaginal catarrh) were significantly negatively associated with relationship satisfaction. The data available for this study do not provide an explanation why urinary bladder infection did not follow the same pattern as the other infections. However, it is well documented that high frequency of sexual intercourse is the most important risk factor for urinary tract infections [45]. A possible explanation for the negative finding in the present study might be that woman reporting poor relationship satisfaction are less sexually active and therefore not exposed to the same risk for bladder infections than their more satisfied counterparts.

Overall, the odds of experiencing an infection for pregnant women with low relationship satisfaction were twice as high compared with pregnant woman reporting high relationship satisfaction. The results support our hypothesis that the level of relationship satisfaction predicts the risk for infectious diseases in pregnancy. These findings are noteworthy because infectious diseases have a potential for harming both the mother and the developing foetus when occurring during pregnancy [14]. Because the present study did not measure couple behaviour or neuropsychological responses related to relationship satisfaction, we cannot conclude how relationship quality influences the risk of infections. However, based on previous research in the general population the present results may be partly explained by the direct immune-impairing effects of hostility and conflicts that more frequently occur in dysfunctional relationships [21,23]. It has also been suggested that partner support may be beneficial because it decreases biological sensitivity to psychological distress [32]. Indeed, emotion-regulation has been linked to activation of the HPA axis and researchers have suggested that emotion-regulation may be a key factor in links between marital quality and health [19,32,46,47]. Anyhow, the direct effect of relationship satisfaction on the level of self-reported infections found in the present study do harmonize with previous research showing that marital quality is linked to biomarkers of stress known to impair immune function [48,49]. Also in line with previous studies [2428], the present results show that stressful life events significantly predicted the risk of infectious diseases.

The hypothesis that relationship quality moderates the adverse effects of stressful life events was not supported by the results. Contrary to our expectations, the results showed a very weak interaction coefficient at a non-significant level between relationship satisfaction and stressful life events on the number of reported infectious diseases. Our hypothesis of interaction was based on previous research indicating that partner support has a moderating effect on biomarkers associated with stress and immune function, such as cortisol and pro-inflammatory cytokines [15,29,32,50]. For example, it was recently demonstrated that effective partner support during pregnancy has the potential to reduce maternal neuroendocrine responses to negative emotional experiences [32]. It should be noted that the present findings are not contradictive to these studies. As we did measure clinical endpoints and not changes in mediating biomarkers, we cannot report on whether relationship quality did moderate stress-related responses or not. We can only conclude that there seem to be no prominent interaction-effect between marital satisfaction and stressful life events on the level of self-reported infections. This is currently a noteworthy finding because the present study is among the first to investigate such a potential interaction-effect on clinical endpoints [34]. This is also the first population-based study to assess the direct association between relationship satisfaction and manifested infectious disease during pregnancy [34]. More comprehensive studies are needed to illuminate how and to what degree the quality of close relationships may moderate the clinical health consequences of chronic stress, as well as documenting central causal pathways between relationship quality and infections [19,51]. One idea would be to utilize blood samples from the current cohort study, and examine immune-related parameters such as cytokines, lymphocytes functions, or telomere length to look for correlations with the present data. This would allow us first to examine whether relationship satisfaction and stressful life events has direct effects on physiological processes and then to examine to what degree individuals who exhibit physiological changes are more likely to develop infectious diseases.

A strength of the present study is its large number of participants; this allows for assessing relative small effects within a narrow confidence interval. Nevertheless, these data must be interpreted with caution. One important limitation is the study’s reliance on self-report questionnaires as the data may be subject to reporting bias. In this respect, the validity and reliability of the outcome measure might be of particular concern. For instance, we cannot know whether the participants based their self-reported diseases on medical diagnoses or self-assessments of experienced symptoms. Moreover, because the respondents were not asked how many times each disease occurred during the 14 weeks period assessed, the current study did not distinguish between single and multiple occurring infections. Nor was it distinguished between mild infections and long-lasting severe infections. It should also be mentioned that the scores of the main study variables were not normally distributed. In small samples this may lead to problems with the interpretation of the statistical tests used in this study. In large samples, however, non-normality of the residuals does not violate the interpretation of significance tests or confidence intervals [52]. Although it may be a concern that only 40% of the invited women consented to participate, a potential impact of selection bias on exposure and outcome variables was evaluated in a previous study [40]. Testing eight different exposure–outcome associations, the authors found no statistically significant differences in association measures between participants in the MoBa and the total population. This indicates that the generalizability of this study is not violated by selection bias.

To conclude, the current study contributes toward a better understanding of the association between relationship quality and manifested infectious disease. The main findings indicate that women with the lowest relationship satisfaction experience about twice as many infectious diseases than women with the highest relationship satisfaction. Although the current findings seem to be clinically interesting it remains to examine how, for whom, and to what degree relationship management and improvement of relationship quality may lead to less infectious diseases [34]. Because very few studies describe associations between relationship quality and clinical endpoints [34], future studies should replicate our findings with the use of subjective self-reports as well as medical diagnoses as outcome variables. To document the causal pathways between relationship quality and infections, a longitudinal study including both biomarkers and clinical endpoints is recommended. Another important next step will be to examine the associations between maternal relationship satisfaction and postpartum outcomes.


We are grateful to all the participating families in Norway who take part in this on-going cohort study.

Author Contributions

Conceived and designed the experiments: REH. Performed the experiments: REH. Analyzed the data: REH TT FT. Contributed reagents/materials/analysis tools: REH TT FT. Wrote the paper: REH.


  1. 1. Rasmussen SA, Jamieson DJ, Uyeki TM (2012) Effects of influenza on pregnant women and infants. Am J Obstet Gynecol 207: S3–S8. doi: 10.1016/j.ajog.2012.06.068. pmid:22920056
  2. 2. Conde-Agudelo A, Villar J, Lindheimer M (2008) Maternal infection and risk of preeclampsia: Systematic review and metaanalysis. Am J Obstet Gynecol 198: 7–22. doi: 10.1016/j.ajog.2007.07.040. pmid:18166297
  3. 3. Brown AS, Derkits EJ (2010) Prenatal infection and schizophrenia: a review of epidemiologic and translational studies. Am J Psychiatry 167: 261–280. doi: 10.1176/appi.ajp.2009.09030361. pmid:20123911
  4. 4. Brown AS (2012) Epidemiologic studies of exposure to prenatal infection and risk of schizophrenia and autism. Dev Neurobiol 72: 1272–1276. doi: 10.1002/dneu.22024. pmid:22488761
  5. 5. Berkman LF, Syme SL (1979) Social networks, host-resistance, and mortality - 9-year follow-up-study of Alameda County residents. Am J Epidemiol 109: 186–204. pmid:425958
  6. 6. Fiorillo D, Sabatini F (2011) Quality and quantity: the role of social interactions in self-reported individual health. Soc Sci Med 73: 1644–1652. doi: 10.1016/j.socscimed.2011.09.007. pmid:22001229
  7. 7. Holt-Lunstad J, Smith TB, Layton JB (2010) Social relationships and mortality risk: a meta-analytic review. PLoS medicine 7: e1000316. doi: 10.1371/journal.pmed.1000316. pmid:20668659
  8. 8. Ben-Shlomo Y, Smith GD, Shipley M, Marmot MG (1993) Magnitude and causes of mortality differences between married and unmarried men. J Epidemiol Community Health 47: 200–205. doi: 10.1136/jech.47.3.200. pmid:8350032
  9. 9. Johnson NJ, Backlund E, Sorlie PD, Loveless CA (2000) Marital status and mortality: The National Longitudinal Mortality Study. Ann Epidemiol 10: 224–238. doi: 10.1136/jech.54.4.254. pmid:10827907
  10. 10. Lindstrom M, Rosvall M (2012) Marital status, social capital and health locus of control: A population-based study. Public Health 126: 790–795. doi: 10.1016/j.puhe.2012.06.001. pmid:22925881
  11. 11. Bookwala J (2005) The role of marital quality in physical health during the mature years. J Aging Health 17: 85–104. doi: 10.1177/0898264304272794. pmid:15601785
  12. 12. Gallo LC, Troxel WM, Matthews KA, Kuller LH (2003) Marital status and quality in middle-aged women: Associations with levels and trajectories of cardiovascular risk factors. Health Psychol 22: 453–463. doi: 10.1037/0278-6133.22.5.453. pmid:14570528
  13. 13. Holt-Lunstad J, Birmingham W, Jones BQ (2008) Is there something unique about marriage? The relative impact of marital status, relationship quality, and network social support on ambulatory blood pressure and mental health. Ann Behav Med 35: 239–244. doi: 10.1007/s12160-008-9018-y. pmid:18347896
  14. 14. Wickrama KAS, Lorenz FO, Wallace LE, Peiris L, Conger RD, et al. (2001) Family influence on physical health during the middle years: The case of onset of hypertension. J Marriage Fam 63: 527–539. doi: 10.1111/j.1741-3737.2001.00527.x
  15. 15. Kiecolt-Glaser JK, Gouin JP, Hantsoo L (2010) Close relationships, inflammation, and health. Neuroscience and Biobehavioral Reviews 35: 33–38. doi: 10.1016/j.neubiorev.2009.09.003. pmid:19751761
  16. 16. Phillips AC, Carroll D, Bums VE, Ring C, Macleod J, et al. (2006) Bereavement and marriage are associated with antibody response to influenza vaccination in the elderly. Brain Behav Immun 20: 279–289. doi: 10.1016/j.bbi.2005.08.003. pmid:16198083
  17. 17. Matthews SG, Phillips DI (2012) Transgenerational inheritance of stress pathology. Exp Neurol 233: 95–101. doi: 10.1016/j.expneurol.2011.01.009. pmid:21281632
  18. 18. Cohen S, Wills TA (1985) Stress, Social Support, and The Buffering Hypothesis. Psychol Bull 98: 310–357. doi: 10.1037/0033-2909.98.2.310. pmid:3901065
  19. 19. Burman B, Margolin G (1992) Analysis of the association between marital relationships and health problems: An interactional perspective. Psychol Bull 112: 39–63. doi: 10.1037/0033-2909.112.1.39. pmid:1529039
  20. 20. Uchino B (2006) Social Support and Health: A Review of Physiological Processes Potentially Underlying Links to Disease Outcomes. J Behav Med 29: 377–387. doi: 10.1007/s10865-006-9056-5. pmid:16758315
  21. 21. Bradbury TN, Fincham FD, Beach SRH (2000) Research on the nature and determinants of marital satisfaction: A decade in review. J Marriage Fam 62: 964–980. doi: 10.1111/j.1741-3737.2000.00964.x
  22. 22. Graham JE, Christian LM, Kiecolt-Glaser JK (2006) Stress, age, and immune function: toward a lifespan approach. J Behav Med 29: 389–400. doi: 10.1007/s10865-006-9057-4. pmid:16715331
  23. 23. Kiecolt-Glaser JK, Loving TJ, Stowell JR, Malarkey WB, Lemeshow S, et al. (2005) Hostile marital interactions, proinflammatory cytokine production, and wound healing. Arch Gen Psychiatry 62: 1377–1384. doi: 10.1001/archpsyc.62.12.1377. pmid:16330726
  24. 24. Gouin J-P, Hantsoo L, Kiecolt-Glaser JK (2008) Immune Dysregulation and Chronic Stress among Older Adults: A Review. Neuroimmunomodulation 15: 251–259. doi: 10.1159/000156468. pmid:19047802
  25. 25. Vedhara K, Cox NKM, Wilcock GK, Perks P, Hunt M, et al. (1999) Chronic stress in elderly carers of dementia patients and antibody response to influenza vaccination. Lancet 353: 627–631. doi: 10.1016/S0140-6736(98)06098-X. pmid:10030328
  26. 26. Burns VE, Carroll D, Drayson M, Whitham M, Ring C (2003) Life events, perceived stress and antibody response to influenza vaccination in young, healthy adults. J Psychosom Res 55: 569–572. doi: 10.1016/S0022-3999(03)00073-4. pmid:14642989
  27. 27. Cohen S, Tyrrell DAJ, Smith AP (1991) Psychological Stress And Susceptibility To The Common Cold. N Engl J Med 325: 606–612. doi: 10.1056/NEJM199108293250903. pmid:1713648
  28. 28. Biondi M, Zannino LG (1997) Psychological stress, neuroimmunomodulation, and Susceptibility to infectious diseases in animals and man: A review. Psychother Psychosom 66: 3–26. doi: 10.1159/000289101. pmid:8996711
  29. 29. Padgett DA, Glaser R (2003) How stress influences the immune response. Trends Immunol 24: 444–448. doi: 10.1016/S1471-4906(03)00173-X. pmid:12909458
  30. 30. Cohen S, Janicki-Deverts D, Doyle WJ, Miller GE, Frank E, et al. (2012) Chronic stress, glucocorticoid receptor resistance, inflammation, and disease risk. Proc Natl Acad Sci U S A 109: 5995–5999. doi: 10.1073/pnas.1118355109. pmid:22474371
  31. 31. Coan JA, Schaefer HS, Davidson RJ (2006) Lending a hand: Social regulation of the neural response to threat. Psychological Science 17: 1032–1039. doi: 10.1111/j.1467-9280.2006.01832.x. pmid:17201784
  32. 32. Giesbrecht GF, Poole JC, Letourneau N, Campbell T, Kaplan BJ, et al. (2013) The Buffering Effect of Social Support on Hypothalamic-Pituitary-Adrenal Axis Function During Pregnancy. Psychosom Med 75: 856–862. doi: 10.1097/PSY.0000000000000004. pmid:24163383
  33. 33. Saxbe DE, Repetti RL, Nishina A (2008) Marital satisfaction, recovery from work, and diurnal cortisol among men and women. Health Psychol 27: 15–25. doi: 10.1037/0278-6133.27.1.15. pmid:18230009
  34. 34. Robles TF, Slatcher RB, Trombello JM, McGinn MM (2014) Marital Quality and Health: A Meta-Analytic Review. Psychol Bull 140: 140–187. doi: 10.1037/a0031859. pmid:23527470
  35. 35. Feldman PJ, Dunkel-Schetter C, Sandman CA, Wadhwa PD (2000) Maternal social support predicts birth weight and fetal growth in human pregnancy. Psychosom Med 62: 715–725. pmid:11020102 doi: 10.1097/00006842-200009000-00016
  36. 36. Hohmann-Marriott B (2009) The couple context of pregnancy and its effects on prenatal care and birth outcomes. Matern Child Health J 13: 745–754. doi: 10.1007/s10995-009-0467-0. pmid:19381792
  37. 37. Rosand GM, Slinning K, Eberhard-Gran M, Roysamb E, Tambs K (2011) Partner relationship satisfaction and maternal emotional distress in early pregnancy. BMC Public Health 11: 12. doi: 10.1186/1471-2458-11-161. pmid:21401914
  38. 38. Stapleton LR, Schetter CD, Westling E, Rini C, Glynn LM, et al. (2012) Perceived partner support in pregnancy predicts lower maternal and infant distress. J Fam Psychol 26: 453–463. doi: 10.1037/a0028332. pmid:22662772
  39. 39. Magnus P, Irgens LM, Haug K, Nystad W, Skjaerven R, et al. (2006) Cohort profile: The Norwegian Mother and Child Cohort Study (MoBa). Int J Epidemiol 35: 1146–1150. doi: 10.1093/ije/dyl170. pmid:16926217
  40. 40. Nilsen RM, Vollset SE, Gjessing HK, Skjaerven R, Melve KK, et al. (2009) Self-selection and bias in a large prospective pregnancy cohort in Norway. Paediatr Perinat Epidemiol 23: 597–608. doi: 10.1111/j.1365-3016.2009.01062.x. pmid:19840297
  41. 41. Blum JS, Mehrabian A (1999) Personality and Temperament Correlates of Marital Satisfaction. J Pers 67: 93–125. doi: 10.1111/1467-6494.00049
  42. 42. Hendrick SS (1988) A Generic Measure of Relationship Satisfaction. J Marriage Fam 50: 93. doi: 10.2307/352430
  43. 43. Snyder DK (1997) Marital Satisfaction Inventory–Revised (MSI-R) manual. Los Angeles: Western Psychological Services.
  44. 44. Mortensen O, Torsheim T, Melkevik O, Thuen F (2012) Adding a Baby to the Equation. Married and Cohabiting Women’s Relationship Satisfaction in the Transition to Parenthood. Fam Process 51: 122–139. doi: 10.1111/j.1545-5300.2012.01384.x. pmid:22428715
  45. 45. Gupta K, Trautner BW (2013) Diagnosis and management of recurrent urinary tract infections in non-pregnant women. BMJ 346: f3140. doi: 10.1136/bmj.f3140. pmid:23719637
  46. 46. Creasey GG, Ladd AA (2004) Negative mood regulation expectancies and conflict behaviors in late adolescent college student romantic relationships: The moderating role of generalized attachment representations. J Res Adolesc 14: 235–255. doi: 10.1111/j.1532-7795.2004.01402005.x
  47. 47. Stadler G, Snyder KA, Horn AB, Shrout PE, Bolger NP (2012) Close relationships and health in daily life: A review and empirical data on intimacy and somatic symptoms. Psychosom Med 74: 398–409. doi: 10.1097/PSY.0b013e31825473b8. pmid:22582337
  48. 48. Graham JE, Glaser R, Loving TJ, Malarkey WB, Stowell JR, et al. (2009) Cognitive word use during marital conflict and increases in proinflammatory cytokines. Health Psychol 28: 621–630. doi: 10.1037/a0015208. pmid:19751089
  49. 49. Kiecolt-Glaser JK, Glaser R, Cacioppo JT, Malarkey WB (1998) Marital stress: Immunologic, neuroendocrine, and autonomic correlates. In: McCann SM, Lipton JM, Sternberg EM, Chrousos GP, Gold PW, et al., editors. Neuroimmunomodulation: Molecular Aspects, Integrative Systems, and Clinical Advances. pp. 656–663.
  50. 50. Hennessy MB, Kaiser S, Sachser N (2009) Social buffering of the stress response: diversity, mechanisms, and functions. Front Neuroendocrinol 30: 470–482. doi: 10.1016/j.yfrne.2009.06.001. pmid:19545584
  51. 51. Kiecolt-Glaser JK, Newton TL (2001) Marriage and health: his and hers. Psychol Bull 127: 472–503. doi: 10.1037/0033-2909.127.4.472. pmid:11439708
  52. 52. Cohen J (2003) Applied multiple regression/correlation analysis for the behavioral sciences. Mahwah, N.J.: L. Erlbaum Associates. 703 p.