The EURO-D is a short scale to measure symptoms of depression, very used in large population surveys. Although there are numerous validation studies, its psychometric properties remain unclear. The two-factor structure (Affective Suffering and Lack of Motivation) is replicated in several studies but with different item compositions, and none reported reliability indices for both factors. For that reason, the aim of this study is to examine the factorial validity of the scale, the reliability of the dimensions, the gender differential item functioning (DIF), and the nomological validity. 46,317 participants aged 50 and over (M = 71.33), from which 57.4 % were females, in Wave 8 of the Survey of Health, Aging and Retirement in Europe (SHARE) were included. EURO-D, R-UCLA, Self-perceived health index, and indicator of taking drugs for anxiety or depression. Factor Analyses, DIF, Reliability Index and Spearman correlations were estimated. Factor analysis identified a bifactor structure: a general factor of Depression and two specific factors of Affective Suffering and Lack of Motivation, which reliabilities were 0.83, 0.83 and 0.79 respectively. No relevant DIF item by gender was found, but higher scores were found in women in all factors. Both factors had positive relations with loneliness, taking drugs and self-perceived health. this study has a cross-sectional design; future research may consider the longitudinal stability of the scale. EURO-D shows adequate psychometric properties when a general factor of depression and two specific factors are considered. Women have higher scores on all dimensions.

Objectives:We aimed to explore the reciprocal effects of social participation, loneliness, and physical inactivity over a period of 6 years in a representative sample of European adults over 50 years old.Design:A longitudinal study with a six-year follow-up period was conducted.Setting:Four waves of the Survey of Health, Ageing and Retirement in Europe project were used.Participants:This study includes 64,887 participants from Europe and Israel, who were aged 50 or older at the first time.Measurements:The relationship between participation in social activities, loneliness and physical inactivity was analyzed, controlling for age, gender, and disability. A series of cross-lagged panel models (CLPMs) were applied to analyze the relationships among these variables.Results:A CLPM with equal autoregressive cross-lagged effects across waves was the best fit to the data (χ2 = 7137.8, CFI = .972, RMSEA = .049, SRMR = .036). The autoregressive effects for the three variables showed high stability across waves, and all the cross-lagged effects in the model were statistically significant. Social activity and physical inactivity maintained a strong negative cross-lagged effect, while their cross-lagged effects on loneliness were comparatively smaller. Social activity had a positive cross-lagged effect on loneliness, while physical inactivity had a negative cross-lagged effect on loneliness.Conclusions:These findings highlight the importance of promoting physical activity and social participation and addressing loneliness through targeted interventions in older adults.

Aim: To study the longitudinal relationship between loneliness and quality of life (QoL) in adults to identify key mechanisms to better design future psychosocial interventions. Method: 13,222 participants from three consecutive waves of the Survey of Health, Ageing, and Retirement in Europe (SHARE), aged 65 or older, 56.3% women. They were analyzed using cross-lagged panel model (CLPM), random intercept cross-lagged panel model (RI-CLPM), and multi-group models disaggregated by gender. Results: The RI-CLPM provided a better fit than the CLPM. Both models showed the stability of QoL and loneliness. All autoregressive paths were significant, and a negative association between concurrent QoL and loneliness was observed across all waves. The CLPM supported a reciprocal relationship, while the RI-CLPM only confirmed the effects of loneliness on QoL. Women reported higher levels of loneliness and poorer QoL, but no gender differences were identified in the longitudinal association. Conclusions: Addressing loneliness in early stages could be a better preventive measure to promote quality of life in both genders.

Objectives: To identify social network profiles using Latent Profile Analysis (LPA), to study the relationships of these profiles with health markers, mental health, quality of life, and cognitive functioning, and to compare profiles across European regions. Methods: 27,272 participants from the Wave 8 of the SHARE project, aged 65 or older (M = 74.95, SD = 7.17) from Europe. Statistical analyses included LPAs followed by MANOVAs to compare the profiles and the health markers. Results: Five profiles were identified: family, friends, spouse, diverse, and others. A no network group was also added. The prevalence of the specific profiles differed across European regions. Individuals with no network and those categorized into the others profile presented the worst health outcomes. Discussion: The “friends” network is more protective toward cognitive functioning and physical health and the “spouse” and “family” ones are more protective toward mental health. The variability according to European regions is discussed.

Background: : Suicide behavior represents a major public health problem for the older population. Within the continuum of suicidal behavior, suicidal ideation may lead to a suicide attempts/death. Risk factors for developing suicidal ideation include mobility limitations, lack of social participation and loneliness. However, there is a need for longitudinal studies to examine these relationships over time. Method: : 50423 older people from three waves of the SHARE project formed the sample (60 years in the first wave; ± = 71.49 ± 8.15; 55% female). Results:: A series of nested Cross-Lagged Panel Models (CLPM) of suicidal ideation, mobility limitations, social participation and loneliness were tested. The best fitting model was that with equal autoregressive and cross-lagged effects across waves (( = 1220.56, CFI = .982, RMSEA = .028, SRMR = .024). The autoregressive effects showed high stability across waves. The cross-lagged effects between suicidal ideation and mobility limitations were strong, while the cross-lagged effects between suicidal ideation and social participation were comparatively smaller. In the case of loneliness, statistical significance was not achieved. Conclusions:: These findings highlight the importance of promoting mobility programs and social activities to prevent suicidal ideation among older adults.

The types of social networks, their prevalence, and their relationship to health outcomes in older age have been different across countries and cultures. Most of the literature has focused on USA or in European countries and little is known about the social network typologies among older adults from Japan. This study aimed to identify these patterns of social network typologies and examine the differences in sociodemographic and related to health variables. 23894 participants from the JAGES project (2019), aged 65 or older (M = 74.74, DT = 6.39) from Japan. Statistical analyses included Latent Profile Analysis (LPA) followed by ANOVAs, Chi square and multinomial logistic regressions tests to compare the profiles. Four profiles were identified: family (66.9%), spouse (16.6%), diverse (14.5%), and neighbor/others (1.9%). The profiles differ statistically (p < 0.001) in all sociodemographic characteristics and in the means of depression, loneliness, self-perceived health, and happiness. Compared with the "family" network, younger men, with fewer chronic illnesses but higher levels of depression and loneliness were more likely to be in the "spouse" profile, older women with lower socioeconomic status, but less lonely and happier in the "diverse" profile and adults who still working, have lower socioeconomic status and are less happy into the "neighbors/others" group. We discuss the differences between the profiles found, the potential differences with previous studies and the specific cultural Japanese nuances that may explain the characteristics of the network types founded.