Four Distinct Health Profiles in Older Patients With Cancer: Latent Class Analysis of the Prospective ELCAPA Cohort

Abstract Aim I examined health/morbidity profiles across 20 countries, determined their associated demographic characteristics and risk factors and compared the distribution of these health/morbidity profiles across countries. Subject and methods I used population-based data drawn from the European Social Survey (N = 20092, 52% female, ages 40+) covering 20 mostly European countries (Austria, Belgium, Czechia, Denmark, Finland, France, Germany, Great Britain, Hungary, Ireland, Israel, Lithuania, Netherlands, Norway, Poland, Portugal, Slovenia, Spain, Sweden and Switzerland) from 2014. Diverse indicators of health/morbidity were used, including self-rated health, self-rated disability, self-reported health problems and mental health symptoms using the CES-D. Latent class analysis was conducted to determine health/morbidity profiles across countries. Results I found that four distinct health profiles best describe overall health/morbidity status in the international sample, each associated with specific demographic and behavioural risk factors: ‘healthy’ profile (62% of participants), ‘unhappy but healthy’ profile (14%), ‘high morbidity, mostly physical’ profile (16%) and ‘high morbidity, mostly psychological’ profile (8%). With few exceptions, participants from Northern Europe and Western Europe were more likely to belong to the ‘healthy’ and the ‘unhappy but healthy’ profiles, whereas participants from Eastern Europe were more likely to belong to the ‘high morbidity, mostly physical’ profile. Distribution of the ‘high morbidity, mostly psychological’ profile appeared to be more uniform across regions. Conclusions Distinct morbidity/health profiles could be identified across countries, and countries varied regarding the relative distribution of these profiles. Specific prevention and treatment consequences associated with each profile are discussed. Future studies should further investigate the patterns of overall health and morbidity in Europe’s populations.

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Latent class analysis differentiation of adjustment disorder and demoralization, more severe depressive and anxiety disorders, and somatic symptoms in patients with cancer

Psycho-Oncology ◽

10.1002/pon.4761 ◽

2018 ◽

Vol 27 (11) ◽

pp. 2623-2630 ◽

Cited By ~ 11

Author(s):

I. Bobevski ◽

D.W. Kissane ◽

S. Vehling ◽

D.P. McKenzie ◽

H. Glaesmer ◽

...

Keyword(s):

Anxiety Disorders ◽

Latent Class Analysis ◽

Latent Class ◽

Somatic Symptoms ◽

Adjustment Disorder ◽

Class Analysis ◽

Patients With Cancer

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Profiles of subjective health among people living alone: a latent class analysis

BMC Public Health ◽

10.1186/s12889-021-11396-2 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Tytti P. Pasanen ◽

Nina Tamminen ◽

Tuija Martelin ◽

Katariina Mankinen ◽

Pia Solin

Keyword(s):

Quality Of Life ◽

Latent Class Analysis ◽

Latent Class ◽

Subjective Health ◽

Living Alone ◽

World Health ◽

Class Analysis ◽

Wide Range ◽

Health Profiles

Abstract Background Living alone has increased globally and especially in Finland where 45% of all households are single occupancy. Epidemiological research has found that living alone a risk factor for a wide range of adversities related to quality of life but the rapidly-changing demographics of people living alone calls for a more detailed investigation of their subjective health status. Methods Using a cross-sectional survey sent for a random sample of Finnish residents in single-person households (n = 884), we explored with latent class analysis whether the respondents form different health profiles based on the three health dimensions defined by the World Health Organization: physical, social, and mental well-being. The identified groups were then compared in terms of demographic characteristics with the χ2 test and quality of life using linear regression models. Sensitivity analyses were run using more refined, manual 3-step BCH method. Results Four distinct health profiles were found: Languishing (4%), Managing (35%), Healthy (30%), and Flourishing (31%). The groups differed in most socio-demographic aspects such as marital and employment status, but not in terms of geographic location or gender (apart from group Languishing that contained more men). Controlling for these socio-demographic differences, all groups showed different average levels of perceived quality of life to the expected direction. Conclusions Our findings suggest that people living alone are indeed a very heterogeneous group in terms of subjective health. Instead of seeing living alone as a mere risk for low quality of life, concept of living alone should be understood more broadly both in public discussion and scientific research.

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