The intention to make preconception lifestyle changes in men: Associated socio-demographic and psychosocial factors

Midwifery 73 (2019) 8–16

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The intention to make preconception lifestyle changes in men: Associated socio-demographic and psychosocial factors Joline Goossens a, Ann Van Hecke a,b, Dimitri Beeckman c,d,e,f,1, Sofie Verhaeghe a,g,1,∗ a

University Centre for Nursing & Midwifery, Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, UZ 5K3, Corneel Heymanslaan 10, B-9000 Ghent, Belgium b Nursing Science, University Hospital Ghent, Corneel Heymanslaan 10, B-9000 Ghent, Belgium c University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Ghent University, Belgium d Skin Integrity Research Group (SKINT), University Centre for Nursing and Midwifery, Department of Public Health and Primary Care, Ghent University, Belgium e School of Health Sciences, Örebro University, Sweden f School of Nursing and Midwifery, Royal College of Surgeons in Ireland, Ireland g VIVES University College, Department Health Care, Wilgenstraat 32, B-8800 Roeselare, Belgium

a r t i c l e

i n f o

Article history: Received 11 July 2018 Revised 4 December 2018 Accepted 11 December 2018

Keywords: ASE model Behavior and behavior mechanisms Associated factors Intention Men Preconception behavior

a b s t r a c t Objective: To determine which socio-demographic and psychosocial factors are associated with the intention for preconception healthily behavioral changes in the general population of reproductive-aged men. Design: A cross-sectional, multicenter study. Setting: Four secondary schools, 4 Public Centers for Social Welfare, 7 Community Health Centers, and online. All data was collected in the X. Participants: A convenience sample of 304 reproductive-aged men were recruited between July 2015 and July 2016. Measurements and Findings: An existing questionnaire was adapted and validated to assess the intention, self-efficacy, attitude, social influence, knowledge, and barriers towards 10 preconception health behaviors. Simple and multiple logistic and linear regression analyses were performed. The overall intention to make preconception lifestyle changes was high (median score: 0.7 on the 0–1 scale). The multiple linear regression revealed that self-efficacy (p < 0.001), social influence of the close social environment (p = 0.02), and attitude (p = 0.05) were associated with a higher intention score. Experiencing negative emotions and beliefs about pre-pregnancy preparations was associated with less intention for preconception health behaviors (p = 0.001). None of the socio-demographic factors was significantly associated with the intention score. Key Conclusions: The overall intention to make preconception lifestyle changes was high, and associated with different psychosocial factors including self-efficacy, social influence, and attitude. Implications for Practice: Preconception interventions should target the identified factors to improve preconception health behaviors in men and negative emotions and beliefs about preconception. Interventions about preconception health care should primarily suggest that men bear the same responsibility as women, which will address the current gender politics and could have -in second instance- a positive outcome on pregnancy outcomes. Because socio-demographic characteristics were of no influence, a general approach should be used. © 2019 Elsevier Ltd. All rights reserved.

Introduction

∗ Corresponding address at: University Centre for Nursing & Midwifery, Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, UZ 5K3, Corneel Heymanslaan 10, B-90 0 0 Ghent, Belgium. E-mail addresses: [email protected] (J. Goossens), Sofi[email protected] (S. Verhaeghe). 1 These authors contributed equally to this work and shared the last authorship.

https://doi.org/10.1016/j.midw.2018.12.006 0266-6138/© 2019 Elsevier Ltd. All rights reserved.

Preconception health care is no new concept, but has been gaining increasing attention in the last four decades (Hood et al., 2007). The interest in preconception health care has risen as it is, for most western countries, an additional opportunity to even further increase healthy pregnancy and enhance birth outcomes (Goodfellow et al., 2017). The basic idea of preconception health care is to assure that couples are healthy before they become

J. Goossens, A. Van Hecke and D. Beeckman et al. / Midwifery 73 (2019) 8–16

pregnant to improve reproductive outcomes (Johnson et al., 2006; World Health Organization, 2012). Moreover, the emphasis on good female health before pregnancy can also be viewed as a political vehicle to get health care to more women in society, which supports women’s autonomy and power (Waggoner, 2017; Withycombe, 2018). The concept is however not without controversy. Although preconception health care originated from a sincere goal of helping to overcome the gap between maternal and reproductive health, and endorsing feminism, it is also claimed that the current overemphasizing of the concept reduces the role of women to mothers (Barnes, 2018; Waggoner, 2017). The latter is mainly the result from the fact that, although preconception guidelines recommend to focus on both women and men (Johnson et al., 2006), little attention has been paid to the role of men (Bodin et al., 2017). Most men (83%) admit to making no preconception lifestyle adjustment to improve health and fertility (Bodin et al., 2017), seemingly placing all the responsibility on women. Next to the fact that involving men in family planning, contraceptive decision making (Frey et al., 2008) or in supporting their spouse’s maternal health behaviors by also changing behavior would reduce these gender politics (Barnes, 2018; Waggoner, 2017), including them in preconception health care could also be important for physical reasons (Frey et al., 2008). Despite a lack of strong evidence (Hemsing et al., 2017), it is suggested that improving men’s health can lead to improved pregnancy outcomes by avoiding damage to the sperm DNA due to environmental (e.g., environmental toxins) and lifestyle influences (e.g., tobacco, alcohol, drugs, or medication), thus avoiding possible sub- or infertility, miscarriage, and birth defects (Frey et al., 2008). Finally, involving men in preconception health care is also a first step to involve men in pregnancy, childbirth, and parenthood, and prepare them for fatherhood (Frey et al., 2008). But so far, few studies have investigated preconception health behavior in men and its associated factors, and most preconception interventions are aimed at women (Hemsing et al., 2017; Toivonen et al., 2017). Such a lack of knowledge is one of the main barriers for midwifes and other healthcare workers to provide adequate preconception care (Goossens et al., 2018). So, in order to include men in preconception care for both physical and societal reasons, more knowledge for practice should be produced starting with gaining more insight into the psychosocial and socio-demographic factors associated with their (intention for) preconception behavior (Bartholomew Eldrigde et al., 2016). Therefore, the goal of this study was to determine which sociodemographic and psychosocial factors are associated with the intention for preconception healthily behavioral changes in the general population of reproductive-aged men. Methods Participants The study used a cross-sectional design with a convenience sample of men aged 15–45, who want to have (more) children, and able to read Dutch or English. Respondents completed an anonymous questionnaire about preconception health and lifestyle changes between July 2015 and July 2016 and were from a variety of settings to obtain a representative sample, including four secondary schools (general/ technical/ vocational secondary education; 4th–7th year), four Public Centers for Social Welfare (‘OCMW’), seven Community Health Centers, and through social media and websites of public agencies and other organizations in X (The X-speaking northern region of X). The study was approved by the Ethical Committee Ethical Committee of the X. Questionnaire The questionnaire was adapted from an existing questionnaire on preconception health and lifestyle changes in women

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(Goossens et al., 2018), derived from the Attitude— Social Influence—Self-efficacy (ASE) model. The ASE-model is a social psychology model that suggests that the intention to perform a certain behavior predicts this behavior. The behavioral intention is in turn determined by three central psychosocial determinants: attitude, social influence, and self-efficacy; and barriers and skills play a role when the actual behavior is attempted (Vries et al., 1988; Vries et al., 1998; Devries and Backbier, 1994; Lechner and Devries, 1995). The final questionnaire consisted of 89 items grouped in seven components: (1) demographics; (2) intention; (3) selfefficacy; (4) attitude; (5) knowledge; (6); barriers; (7) social influence. The barriers component comprised five subgroups: (i) poor health literacy (e.g., not knowing where to find information), (ii) negative emotions and beliefs (e.g., stress due to preconception health information, little control of unborn child, preparing for pregnancy is a woman’s task), (iii) religious beliefs (e.g., religion [Catholicism, Islam, …] as a barrier to make preconception lifestyle changes), (iv) financial issues (e.g., preconception health behaviors are too expensive), and (v) lack of perceived need (e.g., finding yourself healthy enough to conceive without preconception lifestyle adjustments). The social influence component also consisted of five subgroups: (i) social influence of important others (e.g., support from close social environment to make preconception lifestyle changes), (ii) social norm (e.g., other men also prepare for pregnancy), (iii) social influence of healthcare provider (e.g., healthcare providers recommend preconception health behaviors), (iv) social influence of media (e.g., pressured by media to make preconception lifestyle changes), and (v) the importance of other’s opinion regarding preconception health behaviors (e.g. partner, healthcare providers). The questionnaire was available in Dutch and English. The questionnaire, its adaptation process and psychometric properties can be found in supplement 1–3. Procedure To allow optimal access to the target population, three methods were used to recruit participants for this study. Firstly, 11 secondary schools were invited to participate, of which four schools agreed. The teachers distributed the paper questionnaires to the students during class time. The students completed the questionnaire and returned it in a closed envelope. Secondly, posters in waiting rooms of four Public Centers for Social Welfare (‘OCMW’) and seven Community health centers explained the aim of the study. Men were invited to complete the questionnaire while waiting for the appointment, and deposit it in a sealed collection box on site. Thirdly, the questionnaire was available online and was distributed through social media and several websites of public agencies and other organizations. To improve the response rate, one gift voucher of €50 was raffled off among the male participants who completed the online questionnaire. In total, 165 men were recruited through social media and websites, 174 men in class rooms, and 25 men in social welfare centers. Data analysis Data were processed and analyzed using SPSS 21.0 (IBM Corporation, Armonk, NY, USA). Questionnaires with more than 25% missing values were deleted. Descriptive analyses were used to calculate means and medians for continuous variables and proportions for categorical variables. A total preconception behavioral intention and self-efficacy score was calculated through MEANscores of the intention and self-efficacy items. Total attitude, social influence, knowledge, and barrier scores were calculated through SUM-scores.

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J. Goossens, A. Van Hecke and D. Beeckman et al. / Midwifery 73 (2019) 8–16 Table 1 Characteristics of the respondents (n = 304). Variable

Mean (SD)

Median (range)

Age (years) BMI (kg/m²) Ethnicity Immigrantsa Natives Partnership status Relationship No relationship Educationb Low High Paid employmentc Yes No Net household incomec < €2.0 0 0 €2.0 0 0 - €2.999 > €3.0 0 0 Perceived poverty: making ends meet…c , d Easy Difficult Biological children Yes No History of fertility treatmente Yes No Preconception consult before previous pregnancy?e Yes No Desire for children Within one year Longer than one year Smoking Yes No Alcohol use Yes No Serious medical condition Yes No Long-term medication use Yes No

22.0 (6.4) 22.7 (3.8)

19 (15.0 – 42.0) 22.2 (13.9 – 48.4)

45 256

15 85

162 132

54.2 45.8

202 102

66.4 33.6

96 9

91.4 8.6

31 23 51

29.5 21.9 48.6

88 14

86.3 13.7

40 263

13.2 86.8

6 29

17.1 82.9

23 13

63.9 36.1

37 260

12.5 87.5

44 259

14.5 85.5

241 62

79.5 20.5

22 282

7.2 92.8

44 258

14.6 85.4

a

One or both of the parents born outside X. Low level of education: primary, secondary or post-secondary education versus high level of education: college or university education. c Only questioned in non-student population (n = 105). d Perceived poverty was measured by asking “how easy or difficult is it to make ends meet?”. e Only questioned in men who reported having biological children; Abbreviations, BMI, Body Mass Index; SD: standard deviation. b

All ten preconception behavioral intentions were analyzed separately. Simple logistic regression analyses were used to explore socio-demographic and psychosocial factors associated with the intention to perform a preconception behavior. Independent variables with p ≤ 0.10 were included in the multiple logistic regression analysis. Because the overall intention score was not normally distributed, nonparametric tests were applied. Spearman’s rho correlations were used to evaluate associations between the psychosocial factors and overall behavioral intention. Simple linear regression analyses with bootstrapping methods were performed to examine the association between the overall intention score and each psychosocial factor or socio-demographic factor. Independent variables with p ≤ 0.10 were included in the multiple linear regression analysis with bootstrapping methods. The ‘enter’ regression method was used for all regression analyses. Prior to the multiple regression analyses, independent variables were checked for multicollinearity using tolerance values and

variance inflation factor (VIF), but as no independent variable had a tolerance value of more than 0.40, multicollinearity was not considered an issue. The items on income and perceived poverty, and fertility treatment were sub-questions that were skipped if respondents were students or had no biological children, respectively. Because of the high number of missing values for these variables, they were not entered in the multiple model. All tests were two-sided and p < 0.05 was regarded as statistically significant.

Results In total, 364 men completed the questionnaire of who nine did not meet the age criteria, 47 had no desire for (more) children, and four had more than 25% missing values. The final sample comprised 304 men. Their demographic characteristics can be found in Table 1.

J. Goossens, A. Van Hecke and D. Beeckman et al. / Midwifery 73 (2019) 8–16

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Correlation is significant at 0.05 level. Correlation is significant at 0.01 level. ∗∗

∗

14

0.88 (0.17) 17.40 (2.90) 3.35 (1.13) 4.03 (1.13) 2.95 (1.24) 22.98 (3.21) 8.72 (3.34) 10.27 (3.74) 13.59 (4.04) 1.54 (1.06) 2.19 (1.35) 4.37 (1.13) 1.00 (0–1) 17.00 (4–24) 3.00 (1–6) 4.00 (1–6) 3.00 (1–6) 23.00 (8–30) 9.00 (0–16) 10.00 (4–23) 14.00 (5–28) 1.00 (1–6) 2.00 (1–6) 5.00 (1–6)

−0.17∗∗ −0.05 −0.06 −0.11∗ 0.11 0.01 0.12∗ −0.04 −0.14∗ 0.43∗∗ 0.35∗∗ 0.25∗∗

13 12

−0.05 −0.07 −0.18∗∗ 0.06 0.27∗∗ 0.09 0.16∗∗ 0.05 −0.27∗∗ 0.32∗∗ 0.18∗∗ −0.30∗∗ −0.22∗∗ −0.17∗∗ −0.07 0.09 −0.008 0.13∗ −0.02 −0.29∗∗ 0.51∗∗ −0.12∗ −0.09 −0.16∗∗ −0.004 0.20∗∗ 0.10 0.25∗∗ 0.04 −0.30∗∗

10 9

0.08 0.15∗ 0.26∗∗ −0.09 −0.22∗∗ −0.12∗ −0.05 −0.01 0.10 0.08 0.09 0.16∗∗ 0.07 0.10 −0.04

8 7

0.10 0.06 −0.07 0.30∗∗ 0.35∗∗ 0.33∗∗ 0.07 0.26∗∗ 0.03 0.46∗∗ 0.40∗∗

6 5 4 3 2

0.08 0.05 −0.15∗∗ 0.49∗∗

11

Intention to avoid testicular hyperthermia Less than half of the men (n = 136, 45.8%) had the intention to avoid testicular exposure to environmental heat (e.g. sauna or hot baths) during the preconception period. Only self-efficacy to avoid testicular hyperthermia was positively associated with this behavioral intention (Table 3). This model explained 30% of the variance (Nagelkerke R ² = 0.30).

1

Intention to eat healthy Most men (85.2%, n = 253) had the intention to eat healthily during the preconception period. The results (Table 3) showed that higher self-efficacy to adopt healthy eating habits, being sensitive to the social influence of the close social environment, expecting that other men also prepare for pregnancy, age, and being in a relationship increased the odds of intending to eat healthily in the preconception period. Experiencing negative emotions and beliefs about preparing for pregnancy, and smoking decreased the intention to adopt healthy eating habits. This model explained 38% of the variance (Nagelkerke R ² = 0.38).

Table 2 Spearman’s rho correlations and descriptive statistics for all psychosocial variables (n = 304).

Intention to search for information or advice on how to become pregnant in a healthy way Overall, 77.8% (n = 231) of the studied men had the intention to search for information or advice on how to become pregnant in a healthy manner. The results of the multiple logistic regression analysis (Table 3) showed that self-efficacy to search for information or advice and social influence of the close social environment were positively associated with this behavioral intention. Lack of perceived need for preconception health behaviors and religious beliefs as barrier to make preconception lifestyle changes decreased the likelihood of intending to search for information or advice. This model explained 33% of the variance of the intention to search for information or advice (Nagelkerke R ² = 0.33).

0.17∗∗ 0.26∗∗ −0.08

Intention to adopt a healthy lifestyle The majority of the men (n = 255, 85.3%) had the intention to adopt a healthy lifestyle in the preconception period. The results (Table 3) showed that higher self-efficacy to adopt a healthy lifestyle and more social influence of the close social environment increased the odds of intending to adopt a healthy lifestyle. Experiencing negative emotions and beliefs about preparing for pregnancy, such as stress and the belief that preconception health care is a medicalization of conception decreased the likelihood of this behavioral intention. Age was positively associated, while smoking was negatively associated with the intention to adopt a healthy lifestyle preconceptionally. Overall, this model explained 23% of the variance (Nagelkerke R ² = 0.23).

0.36∗∗ 0.15∗

Preconception health behaviors: associated socio-demographic and psychosocial factors

1. Intention (overall score) 0.27∗∗ 2. Attitude 3. Self-efficacy (overall score) 4. Social influence close environment 5. Social norm 6. Social influence healthcare providers 7. Social influence media 8. Importance of others’ opinion 9. Knowledge 10. Barriers: health literacy 11. Barriers: emotions and beliefs 12. Barriers: religion 13. Barriers: financial 14. Barriers 5: perceived need Mean (SD) 0.71 (0.22) 14.82 (3.00) Median (range) 0.71 (0–1) 15,00 (4–21)

Table 2 shows that men had a positive attitude and high selfefficacy towards preparing for pregnancy. Furthermore, men were most sensitive to social influences of healthcare providers and their close social environment. The opinion of the (future) partner about preparing for pregnancy was assessed as most important, followed by the opinion of healthcare providers. The total knowledge score was moderate. The knowledge about tobacco, alcohol, and drug abuse was high and contrasted with the low knowledge about folic acid, vaccination, and preventive measures for foodborne infections. Overall, most men experienced few barriers regarding preconception lifestyle changes. The most reported barrier was the lack of perceived need for preconception health behaviors.

−0.13∗ −0.19∗∗ −0.05 0.05 −0.04 −0.04 −0.10 0.04 0.06 −0.05 −0.01 −0.001 −0.04

Psychosocial factors

12

J. Goossens, A. Van Hecke and D. Beeckman et al. / Midwifery 73 (2019) 8–16

Table 3 Summary of multiple logistic regression analysisa for socio-demographic and psychosocial factors associated with individual preconception behavioral intentions. Variable

B

SE

P value

OR

95% CI

Intention to adopt a healthy lifestyle (n = 282) Attitude Self-efficacy to adopt a healthy lifestyle Social influence close social environment Barrier: emotions and beliefs Age Education: high Smoking: yes

0.07 1.73 0.18 −0.14 0.10 −0.18 −1.46

0.07 0.82 0.07 0.05 0.05 0.59 0.47

0.32 0.03∗ 0.01∗ 0.007 0.04∗ 0.76 0.002

1.07 5.67 1.20 0.87 1.11 0.83 0.23

0.94 – 1.22 1.15 – 27.99 1.04 – 1.38 0.78 – 0.96 1.01 – 1.22 0.27 – 2.62 0.09 – 0.59

Intention to search for information or advice on how to become pregnant in a healthy way (n = 268) Attitude 0.04 0.07 0.55 Self-efficacy to search information/advice 2.81 0.64 <0.001∗∗ Social influence close social environment 0.16 0.07 0.02∗ Social influence healthcare providers 0.12 0.19 0.51 Knowledge −0.008 0.07 0.91 Barrier: health literacy −0.02 0.06 0.70 Barrier: emotions and beliefs −0.07 0.06 0.23 Barrier: religion −0.44 0.19 0.02∗ Barrier: financial −0.16 0.14 0.26 Barrier: perceived need −0.37 0.19 0.047 Education: high −0.56 0.45 0.21

1.04 16.55 1.18 1.13 0.99 0.98 0.94 0.64 0.85 0.69 0.57

0.91 – 1.19 4.75 – 57.73 1.02 – 1.35 0.78 – 1.65 0.87 – 1.13 0.86 – 1.10 0.84 – 1.04 0.44 – 0.94 0.65 – 1.12 0.48 – 0.99 0.24 – 1.37

Intention to eat healthily (n = 266) Attitude Self-efficacy to eat healthily Social influence close social environment Social norm Importance of other’s opinion Knowledge Barrier: emotions and beliefs Age Education: high Relationship: yes Smoking: yes

0.07 3.36 0.21 0.52 0.11 −0.09 −0.19 0.26 0.66 1.19 −1.98

0.08 1.12 0.10 0.26 0.07 0.09 0.06 0.08 0.76 0.56 0.60

0.41 0.003∗ 0.04∗ 0.04∗ 0.12 0.29 0.003∗ 0.001∗ 0.39 0.03∗ 0.001∗

1.07 28.64 1.23 1.69 1.12 0.91 0.83 1.30 1.93 3.29 0.14

0.91 – 1.25 3.18 – 258.01 1.01 – 1.50 1.01 – 2.82 0.97 – 1.29 0.77 – 1.08 0.73 – 0.94 1.11 – 1.53 0.43 – 8.62 1.11 – 9.76 0.04 – 0.44

Intention to avoid testicular hyperthermia (n = 267) Attitude Self-efficacy to avoid hyperthermia Social influence close social environment Barrier: emotions and beliefs Barrier: financial Ethnicity: natives BMI: overweight/obesity

0.07 3.34 0.08 −0.02 −0.11 −0.32 0.57

0.05 0.74 0.05 0.04 0.12 0.44 0.35

0.19 <0.001∗ 0.10 0.59 0.37 0.46 0.10

1.07 28.29 1.08 0.98 0.90 0.72 1.77

0.97 6.63 0.98 0.91 0.72 0.31 0.89

0.43 <0.001∗∗ 0.15 0.34 0.05∗ 0.14 0.08 0.89 0.02

1.04 137.45 1.08 1.05 0.93 0.81 0.95 1.07 14.61

0.94 – 1.16 12.43 – 1519.95 0.97 – 1.19 0.95 – 1.17 0.86 – 1.00 0.62 – 1.07 0.90 – 1.01 0.39 – 2.92 1.54 – 138.32

Intention to attend a preconception consult with a healthcare provider (n = 279) Attitude 0.04 0.06 Self-efficacy to attend a PC consult 4.92 1.23 Social influence close social environment 0.08 0.05 Importance of other’s opinion 0.05 0.05 Barriers: emotions and beliefs −0.08 0.04 Barriers: perceived need −0.21 0.14 Age −0.05 0.03 Biological children: yes 0.07 0.51 Serious medical condition: yes 2.68 1.15 Intention to support the partner to perform preconception lifestyle changes (n = 286) Attitude 0.05 0.16 Self-efficacy to support the partner – – 0.21 0.17 Social influence close social environment Social influence healthcare providers 0.76 0.54 Barrier: religion −0.93 0.42 Intention to stop smoking (n = 42) Self-efficacy to stop smoking 1.32 1.09 Barrier: emotions and beliefs −0.17 0.11 Barrier: perceived need −0.30 0.33 Education: high 1.51 0.91 Biological children: yes 1.41 0.90 Intention to reduce alcohol consumption (n = 229) Attitude Self-efficacy to reduce drinking alcohol Age Intention to lose weight (n = 57) Self-efficacy to lose weight Social influence media Age Education: high

– – – – – – –

1.18 120.63 1.19 1.05 1.13 1.72 3.51

0.74 0.99 0.21 0.16 0.03∗

1.05 0.00 1.24 2.14 0.40

0.77 – 1.44 – 0.89 – 1.72 0.74 – 6.20 0.18 – 0.90

0.23 0.13 0.37 0.10 0.12

3.74 0.85 0.74 4.54 4.10

0.44 0.68 0.39 0.76 0.70

– – – – –

31.58 1.05 1.42 27.18 29.91

0.17 3.77 −0.05

0.06 0.75 0.03

0.003∗ <0.001∗∗ 0.049∗

1.19 43.32 0.95

1.06 – 1.33 10.00 – 187.84 0.90 – 1.00

3.48 0.76 0.11 −1.04

1.30 0.35 0.08 0.85

0.008∗ 0.03∗ 0.17 0.22

32.40 2.13 1.11 0.36

2.53 – 415.45 1.08 – 4.20 0.95 – 1.30 0.07 – 1.89

0.23 0.09 0.08

1.17 0.54 5.38

0.91 – 1.50 0.26 – 1.09 0.84 – 34.58

Intention to discuss medication or herb use with healthcare provider (n = 44) Importance of other’s opinion 0.15 0.13 Barrier: perceived need −0.63 0.36 Alcohol: yes 1.68 0.95

a All variables with a p-value of ≤ 0.10 in the simple regression analysis were included;. Abbreviations, B: Beta; BMI, Body Mass Index; CI, confidence interval; SE, standard error; OR, odds ratio; PC, preconception. ∗ Significance at 0.05 level. ∗∗ Significance at 0.01 level.

J. Goossens, A. Van Hecke and D. Beeckman et al. / Midwifery 73 (2019) 8–16

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Table 4 Summary of multiple linear regression analysisa with bootstrapping methods (10 0 0 0 bootstrapping samples) for socio-demographic and psychosocial factors associated with the overall intention to make preconception lifestyle changes (n = 280). Variable

B

SE

P value

95% CI

Attitude Self-efficacy (overall score) Social influence close social environment Social norm Social influence media Barrier: emotions and beliefs Barrier: financial Barrier: perceived need Desire for children: longer than one year

0.01 0.39 0.01 0.02 0.01 −0.01 −0.01 −0.01 −0.06

0.004 0.10 0.005 0.01 0.01 0.003 0.01 0.01 0.03

0.05∗ <0.001∗ ∗ 0.02∗ 0.24 0.28 0.001∗ 0.29 0.27 0.07

0.00 – 0.02 0.21 – 0.59 0.002 – 0.02 −0.02 – 0.04 −0.01 – 0.03 −0.02 – −0.01 −0.03 – 0.01 −0.04 – 0.01 −0.12 – 0.01

a All variables with a p value of ≤0.10 in the simple regression analysis were included; Abbreviations, B: Beta; CI, confidence interval; SE, standard error. ∗ Significance at 0.05 level. ∗∗ Significance at 0.01 level.

Intention to attend a preconception consult with a healthcare provider Approximately half of the men (n = 152, 51.5%) intended to consult a healthcare provider for preconception care. The results show (Table 3) that higher self-efficacy to attend a preconception consult and having a serious medical condition increased the likelihood of intending to consult a healthcare provider in the preconception period, while experiencing negative emotions and beliefs about preparing for pregnancy decreased the odds for this behavioral intention. This model explained 38% of the variance (Nagelkerke R ² = 0.38). Intention to support the partner to perform preconception lifestyle changes Almost all men (97.6%, n = 290) had the intention to support their partner to adopt preconception lifestyle changes. The results show (Table 3) that only religious beliefs as a barrier to making preconception lifestyle changes were negatively associated with the intention to support the partner. This model explained 27% of the variance (Nagelkerke R ² = 0.27). Intention to stop smoking Forty-four men (14.5%) reported that they were smokers. Twenty-five men (58.1%) had the intention to stop smoking in the preconception period. None of the independent variables remained significantly associated with this behavioral intention (Table 3). This model explained 39% of the variance (Nagelkerke R ² = 0.39). Intention to reduce alcohol consumption Four in five men (n = 241) consumed alcohol, of whom 41.5% (n = 100) intended to reduce the alcohol consumption in the preconception period. The results showed that having a positive attitude towards preparing for pregnancy and higher self-efficacy to reduce drinking alcohol increased the likelihood of this behavioral intention, while age decreased the likelihood of reducing alcohol consumption in the preconception period (Table 3). This model explained 38% of the variance (Nagelkerke R ² = 0.38). Intention to lose weight Twenty per cent of the men (n = 59) had Body Mass Index above 25 kg/m². Less than half of this subgroup (43.9%, n = 25) intended to lose weight preconceptionally. The results of the multiple logistic regression analysis showed that higher self-efficacy to lose weight and experiencing social pressure from the media to make preconception lifestyle changes increased the likelihood of this behavioral intention (Table 3). This model explained 52% of the variance (Nagelkerke R ² = 0.52).

Intention to discuss medication or herb use with healthcare provider Forty-four men (14.6%) indicated long-term medication use, of which anti-allergic (n = 13), endocrine (n = 8), and psychostimulant (n = 6) drugs were most frequently reported. Twenty-four (54.5%) of this subgroup had the intention to discuss medication use with a healthcare provider in the preconception period. None of the variables were significantly associated with the intention to discuss medication or herb use with a healthcare provider in the preconception period (Table 3). This model explained 26% of the variance (Nagelkerke R ² = 0.26). Overall intention to make preconception lifestyle changes: associated socio-demographic and psychosocial factors Table 2 showed that the overall preconception behavioral intention score was high and that self-efficacy, attitude, and social influence from the close social environment were positively associated with the intention to make preconception lifestyle changes. Moreover, the strongest barrier to make preconception lifestyle changes was having negative emotions and beliefs about pre-pregnancy preparations. No other factors were associated with the overall intention score. The results of the multiple linear regression analysis (Table 4) indicated that self-efficacy and social influence of the close social environment were positively associated with the intention to make preconception lifestyle changes. The experience of negative emotions and beliefs about pre-pregnancy preparations was negatively associated with the intention to make preconception lifestyle changes. A positive attitude was also positively associated with a higher intention to make preconception lifestyle changes, but the association was only borderline significant. This model explained 24% of the variance of the intention to make preconception lifestyle changes (R² = 0.27, adjusted R² = 0.24). Discussion To the best of our knowledge, this was the first study to explore socio-demographic and psychosocial factors associated with the intention to make preconception lifestyle changes in men. To date, very few preconception health interventions and studies are focused on men (Toivonen et al., 2017). Therefore, this study was only a first step and further research is needed. After the methodological considerations, insights for practice and recommendations for intervention development are given. Methodological considerations Major strengths of this study are the multicenter recruitment and the comprehensive assessment with a validated questionnaire.

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Although this research extends our knowledge of preconception health behaviors in men and nuances it, there are several limitations that should be mentioned. First, the sample consisted of mostly self-selected men (with the exception of the male students who were recruited through secondary schools), was of young age, and limited to men who understand written Dutch or English. Consequently, there was a lower proportion of men with a foreign nationality and a higher proportion of educated men in comparison to the general population. Therefore, these findings may be less generalizable to men with foreign nationality and the lower educated non-student male population. Therefore, these findings may be less generalizable to men with foreign nationality and the lower educated non-student male population. The selection process in this study was driven by the willingness to be included of the centers that we invited. Therefore, our sample was a convenience sample and no purposive sample. Again, the underrepresentation of non-educated men or non-student members of society shows that it difficult to reach this population group (Hemsing et al., 2017). Second, although the intention is viewed as primary determinant of behavior, actual behavior would have been a more accurate outcome variable (Vries et al., 1988; Vries et al., 1998; Devries and Backbier, 1994; Lechner and Devries, 1995). Third, this study has a cross-sectional design, which does not allow determination of the causal direction of the findings. Therefore, future studies should use a longitudinal design to assess whether psychosocial factors and intention have an influence on preconception lifestyle adjustments in men. Fourth, the list of preconception health behaviors was limited to ten, and whereof some are controversial due to limited and/or conflicting data (e.g., impact of environmental testicular hyperthermia on the male fertility; Momen et al., 2010; Rao et al., 2015). Fifth, preconception behavioral intention and self-efficacy were measured and studied as dichotomous, single-item variables, which is most likely an oversimplification of complex psychosocial constructs. In combination with the high odds ratios and broad confidence intervals that were observed for self-efficacy, perhaps due to low cell frequencies in some of the categories, the actual strength of the association between intention and self-efficacy needs to be interpreted with caution. Therefore, these findings must be interpreted cautiously.

for losing weight and reducing alcohol consumption. This contrasts with the study of Bodin et al. (2017) who found that reducing or quitting consumption of alcohol and increasing exercise were the most common preconception lifestyle adjustments. Second, self-efficacy, social influence of the close social environment, and attitude towards preparing for pregnancy were positively associated with the overall intention to make preconception lifestyle changes. The importance of self-efficacy for health behaviors or behavioral intentions (Bassett-Gunter et al., 2013; Goossens et al., 2018; Lechner et al., 2002; Masters et al., 2017), the close social environment on the intention of making preconception lifestyle changes as sole social influence (Goossens et al., 2018), and that the only significant barrier to the intention to make preconception lifestyle changes was the experience of negative emotions and beliefs about preparing for pregnancy (i.e., stress, lack of control over the health of an unborn child, medicalization of the conception, the perception that becoming pregnant in a healthy way is a woman’s task, and lack of time or energy) is similar to previous finding amongst women (Goossens et al., 2018; Poels et al., 2016). Third, knowledge about preconception health and fertility was not associated with the intention to make preconception lifestyle changes, a fact that has been both proven (Delissaint and McKyer, 2011; Temel et al., 2013), but also rejected (Goossens et al., 2018) by previous studies amongst women. The high knowledge about the influence on fertility and pregnancy of tobacco, alcohol, and drug use, and the low knowledge about folic acid, vaccination, and preventive measures for foodborne infections is consistent with previous studies in men and women (Charafeddine et al., 2014; Frey et al., 2012; Goossens et al., 2018), but is important to mention that women’s knowledge scores were still higher compared to those of men (Charafeddine et al., 2014; Mitchell et al., 2012; Temel et al., 2015). Fourth, no associations were found between socio-demographic factors and the overall intention to make preconception lifestyle changes. Fifth, our models could explain half of the variances at best. This indicates that other factors, next to socio-demographic factors and psychosocial factors, may be more important influences on these behavioral intentions (Lechner et al., 1997).

Insights for practice Recommendations for future intervention development This study explored the socio-demographic and psychosocial factors associated with the intention to make preconception health behaviors amongst the general population of reproductive men. As elaborated in the introduction, including men in preconception health could be improve pregnancy outcomes and could reduce the exclusiveness of the responsibility for healthy pregnancy and birth for women. The aim is therefore to inform practice of the factors that could influence the inclusion of men in preconception health care. This study provides five important insights for the future design of preconception interventions for both men and women. First, our findings showed that men had a high overall intention to make preconception lifestyle changes. This contrasts with the fact that only 17% of the fathers reported an actual lifestyle adjustment in preparation of pregnancy (Bodin et al., 2017). Although, the ASE model assumes that behavior is determined by the behavioral intention to perform it (Vries et al., 1988; Vries et al., 1998), intention will not always lead to behavioral change due to other factors like the absence of skills (e.g. knowledge, coping skills) or the presence of barriers (e.g. financial barriers, time, energy). This is reflected in the comparison between the intention rates in our study and results on actual behavioral change in a previous study. Our study found high intention rates for supporting the partner to adopt a healthy lifestyle in the preconception period, adopting a healthy lifestyle, and eating healthily and low intention rates

Based on these insights, preconception health care intervention amongst men should focus on self-efficacy, social influence of the close social environment and decreasing the negative emotions and believes on pregnancy. A combination of both modeling (i.e, the provision of an appropriate model to reinforce the desired behavior) and providing information about other’s approval (i.e., provision of information about what other people think about the behavior and whether others will approve or disapprove the behavioral change) can be a good strategy to support men’s self-efficacy and increase the positive impact of the social influence of the close social environment and to make preconception lifestyle changes (Kok et al., 2016). A possible practical translation of this strategy is the use of role-model stories including peers that are reinforced for preconception health behaviors. For instance, one application for information about other’s approval could be a health message with a conversation between a pregnant woman and her friends, emphasizing and praising the support of her partner and his preconception lifestyle changes. The findings also show which behavior that should be avoided. Although that healthcare providers are the preferred source of preconception health information and care (Frey et al., 2012; Frey and Files, 2006; Goossens et al., 2016), healthcare providers did not have a significant influence on the intention to make preconcep-

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tion lifestyle changes. Therefore, using your status as health care professional to make people change their behavior will not have any (or a negative) effect. Finally, as knowledge is shown to have no influence, mass media and social media campaigns (Lassi et al., 2014; Poels et al., 2017) to increase knowledge may not have the intended effect. Finally, the fact that negative emotions and believes on pregnancy are a significant barrier on the intention change preconception behavior should be discussed. It should be acknowledged that these believes and emotions are closely related to medicalization of the conception and the perception that becoming pregnant in a healthy way is a woman’s task. This fact, in combination with the differences found between intention and actual behavioral change, and the low predictive value of our models, also relativize the concept of preconception health care for men and women as a mean to improve pregnancy outcomes. The methods that can be used to change attitude and negative emotions and beliefs about preconception, like arguments (i.e., using meaningful premises and a conclusion) and cultural similarity (i.e., using characteristics of the target group in message) should primarily suggest that parenthood starts before conception, and that male health and involvement in the preconception period are equally important and that they bear the same responsibility as women. Because socio-demographic characteristics were of no influence, no specific groups should be targeted. Such a general approach will address the current gender politics, as described in the introduction, and could have -in second instance- a positive outcome on pregnancy outcomes. Conflict of interest None declared. Ethical approval The study was approved by the Ethical Committee of Ghent University Hospital (B670201422053 & B670201524584) on the 5th of June 2015. Every questionnaire included an information letter, explaining both the context and the aim of the study. All participants provided written informed consent. Funding sources This study was funded by The Research Foundation – Flanders (FWO) (grant number G058113N), the agency that supports innovative fundamental and strategic research at the universities of the Flemish Community. FWO did not have any role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. Acknowledgments The authors wish to thank all men that participated in our study. This study was funded by the Research Foundation Flanders (FWO) (grant number G058113N). References Barnes, M.W., 2018. Book Review: The Zero Trimester: Pre-pregnancy Care and the Politics of Reproductive Risk By Miranda R. Waggoner. SAGE Publications Sage CA, Los Angeles, CA. Bartholomew Eldrigde, L.K., Markham, C.M., Ruiter, R.A.C., Fernandez, M.E., Kok, G., Parcel, G.S., 2016. Planning Health Promotion Programs: an Intervention Mapping Approach, Fourth ed. Wiley & Sons, Hoboken, NJ. Bassett-Gunter, R.L., Levy-Milne, R., Naylor, P.J., Symons Downs, D., Benoit, C., Warburton, D.E., Rhodes, R.E., 2013. Oh baby! Motivation for healthy eating during parenthood transitions: A longitudinal examination with a theory of planned behavior perspective. Int. J. Behav. Nutr. Phys. Act 10, 88. doi:10.1186/ 1479- 5868- 10- 88.

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