A healthy lifestyle can support future sexual satisfaction: results from a 9-year longitudinal survey.

BACKGROUND: Previous follow-up studies have demonstrated the association between good health behavior and good sexual functioning for men, but the longitudinal relationship between multiple health behaviors and satisfaction with sex life remains understudied. AIM: The aim of the study was to explore whether good health behavior associates with improved satisfaction with sex life for men and women in a follow-up of 9 years. METHODS: This cohort study utilized survey data from the population-based Health and Social Support study. It includes responses from 10 671 working-aged Finns. Using linear regression models, we examined a composite sum score representing 4 health behaviors (range, 0-4) in 2003 as a predictor of satisfaction with sex life in 2012. The analyses adjusted for various covariates in 2003, including satisfaction with sex life, living status, age, gender, education, number of diseases, and importance of sex life in 2012. OUTCOMES: The outcome in the study was satisfaction with sex life in the year 2012. RESULTS: Participants who exhibited better health behavior at baseline demonstrated improved satisfaction with sex life when compared with those with poorer health behavior (ß = -0.046, P = .009), even when controlling for the aforementioned covariates. The positive effect of reporting all beneficial health behaviors vs none of them was greater than having none vs 3 chronic conditions. Furthermore, this was almost half the effect of how satisfaction with sex life in 2003 predicted its level in 2012. These findings were supported by an analysis of the congruence of health behavior in the observation period from 2003 to 2012 predicting changes in satisfaction with sex life. CLINICAL IMPLICATIONS: The results could serve as a motivator for a healthy lifestyle. STRENGTHS AND LIMITATIONS: The current study used a longitudinal large sample and a consistent survey procedure, and it explored the personal experience of satisfaction instead of sexual function. However, the study is limited in representing today's diversity of gender, since the options for gender at the time of survey were only male and female. CONCLUSION: These findings indicate that engaging in healthy behaviors contributes to the maintenance and enhancement of satisfaction with sex life over time.

Do Patients' Psychosocial Characteristics Impact Antibiotic Prescription Rates?

Previous research suggests that the characteristics of both patients and physicians can contribute to the overuse of antibiotics. Until now, patients' psychosocial characteristics have not been widely explored as a potential contributor to the overuse of antibiotics. In this study, the relationship between a patient's psychosocial characteristics (self-reported in postal surveys in 2003) and the number of antibiotics they were prescribed (recorded in Finnish national registry data between 2004-2006) were analyzed for 19,300 working-aged Finns. Psychosocial characteristics included life satisfaction, a sense of coherence, perceived stress, hostility, and optimism. In a structural equation model, patients' adverse psychosocial characteristics were not related to increased antibiotic prescriptions in the subsequent three years. However, these characteristics were strongly associated with poor general health status, which in turn was associated with an increased number of subsequent antibiotic prescriptions. Furthermore, mediation analysis showed that individuals who used healthcare services more frequently also received more antibiotic prescriptions. The current study does not support the view that patients' adverse psychosocial characteristics are related to an increased number of antibiotic prescriptions. This could encourage physicians to actively discuss treatment options with their patients.

Changed health behavior improves subjective well-being and vice versa in a follow-up of 9 years.

BACKGROUND: Previous research on health behavior and subjective well-being has mainly focused on interindividual differences or explored certain domains of health behavior. Good health behavior and subjective well-being at baseline can predict each other after a follow-up. In the present cohort study, we explored the outcomes of change for an individual i.e., how changed health behavior is reflected in subsequent subjective well-being and vice versa. METHODS: Data (n = 10,855) originates from a population-based Health and Social Support (HeSSup) study on working-age Finns in 2003 and 2012. A composite measure of health behavior included physical activity, dietary habits, alcohol consumption, and smoking status (range 0-4, worst-best) and a composite measure of subjective well-being (with reversed scoring) included three life assessments, i.e., interest, happiness, and ease in life, and perceived loneliness (range 4-20, best-worst). Different multiple linear regression models were used to study how changes in health behavior predict subjective well-being and the opposite, how changes in subjective well-being predict health behavior. RESULTS: A positive change in health behavior from 2003 to 2012 predicted better subjective well-being (i.e., on average 0.31 points lower subjective well-being sum score), whereas a negative change predicted poorer subjective well-being (i.e., 0.37 points higher subjective well-being sum score) (both: p < 0.001) compared to those study subjects who had no change in health behavior. Similarly, when a positive and negative change in subjective well-being was studied, these figures were 0.071 points better and 0.072 points worse (both: p < 0.001) health behavior sum score, respectively. When the magnitude of the effect of change was compared to the range of scale of the outcome the effect of health behavior change appeared stronger than that of subjective well-being. CONCLUSION: Changes in health behavior and subjective well-being have long-term effects on the level of the other, the effect of the first being slightly stronger than vice versa. These mutual long-term benefits can be used as a motivator in health promotion on individual and societal levels.

Health behavior of working-aged Finns predicts self-reported life satisfaction in a population-based 9-years follow-up.

BACKGROUND: Previous studies have shown positive association between health behavior and life satisfaction, but the studies have mostly been cross-sectional, had follow-up times up to 5 years or focused on only one health behavior domain. The aim of the study was to explore how principal health behavior domains predict life satisfaction as a composite score in a previously unexplored longitudinal setting. METHODS: The present study tested whether a health behavior sum score (range 0-4) comprising of dietary habits, smoking, alcohol consumption, and physical activity predicted subsequent composite score of life satisfaction (range 4-20). Data included responses from 11,000 working-age Finns who participated in the Health and Social Support (HeSSup) prospective population-based postal survey. RESULTS: Protective health behavior in 2003 predicted (p < .001) better life satisfaction 9 years later when sex, age, education, major diseases, and baseline life satisfaction were controlled for. The ß in the linear regression model was - 0.24 (p < .001) corresponding to a difference of 0.96 points in life satisfaction between individuals having the best and worst health behavior. CONCLUSION: Good health behavior has a long-term beneficial impact on subsequent life satisfaction. This knowledge could strengthen the motivation for improvement of health behavior particularly on an individual level but also on a policy level.

Longitudinal stability and interrelations between health behavior and subjective well-being in a follow-up of nine years.

BACKGROUND: The bidirectional relationship between health behavior and subjective well-being has previously been studied sparsely, and mainly for individual health behaviors and regression models. In the present study, we deepen this knowledge focusing on the four principal health behaviors and using structural equation modeling with selected covariates. METHODS: The follow-up data (n = 11,804) was derived from a population-based random sample of working-age Finns from two waves (2003 and 2012) of the Health and Social Support (HeSSup) postal survey. Structural equation modeling was used to study the cross-sectional, cross-lagged, and longitudinal relationships between the four principal health behaviors and subjective well-being at baseline and after the nine-year follow-up adjusted for age, gender, education, and self-reported diseases. The included health behaviors were physical activity, dietary habits, alcohol consumption, and smoking status. Subjective well-being was measured through four items comprising happiness, interest, and ease in life, and perceived loneliness. RESULTS: Bidirectionally, only health behavior in 2003 predicted subjective well-being in 2012, whereas subjective well-being in 2003 did not predict health behavior in 2012. In addition, the cross-sectional interactions in 2003 and in 2012 between health behavior and subjective well-being were statistically significant. The baseline levels predicted their respective follow-up levels, the effect being stronger in health behavior than in subjective well-being. CONCLUSION: The four principal health behaviors together predict subsequent subjective well-being after an extensive follow-up. Although not particularly strong, the results could still be used for motivation for health behavior change, because of the beneficial effects of health behavior on subjective well-being.

Subjective well-being predicts health behavior in a population-based 9-years follow-up of working-aged Finns.

The cross-sectional association between measures of subjective well-being (SWB) and various health behaviors is well-established. In this 9-year (2003-2012) follow-up study, we explored how a composite indicator of SWB (range 4-20) with four items (interest, happiness, and ease in life, as well as perceived loneliness) predicts a composite health behavior measure (range 0-4) including dietary habits, physical activity, alcohol consumption, and smoking status. Study subjects (n = 10,855) originated from a population-based random sample of working-age Finns in the Health and Social Support study (HeSSup). According to linear regression analysis, better SWB predicted better health behavior sum score with a ß = 0.019 (p < 0.001) with a maximum effect of 0.3 points after adjusting for age (p = 0.038), gender (p < 0.001), education (p = 0.55), baseline self-reported diseases (p = 0.020), baseline health behavior (ß = 0.49, p < 0.001), and the interaction between SWB and education (p < 0.001). The results suggest that SWB has long-term positive effect on health behavior. Thus, interventions aiming at health behavioral changes could benefit from taking into account SWB and its improvement in the intervention.