Multimorbidity patterns in low-middle and high income regions: a multiregion latent class analysis using ATHLOS harmonised cohorts

ObjectivesOur aim was to determine clusters of non-communicable diseases (NCDs) in a very large, population-based sample of middle-aged and older adults from low- and middle-income (LMICs) and high-income (HICs) regions. Additionally, we explored the associations with several covariates.DesignThe total sample was 72 140 people aged 50+ years from three population-based studies (English Longitudinal Study of Ageing, Survey of Health, Ageing and Retirement in Europe Study and Study on Global Ageing and Adult Health) included in the Ageing Trajectories of Health: Longitudinal Opportunities and Synergies (ATHLOS) project and representing eight regions with LMICs and HICs. Variables were previously harmonised using an ex-post strategy. Eight NCDs were used in latent class analysis. Multinomial models were made to calculate associations with covariates. All the analyses were stratified by age (50–64 and 65+ years old).ResultsThree clusters were identified: ‘cardio-metabolic’ (8.93% in participants aged 50–64 years and 27.22% in those aged 65+ years), ‘respiratory-mental-articular’ (3.91% and 5.27%) and ‘healthy’ (87.16% and 67.51%). In the younger group, Russia presented the highest prevalence of the ‘cardio-metabolic’ group (18.8%) and England the ‘respiratory-mental-articular’ (5.1%). In the older group, Russia had the highest proportion of both classes (48.3% and 9%). Both the younger and older African participants presented the highest proportion of the ‘healthy’ class. Older age, being woman, widowed and with low levels of education and income were related to an increased risk of multimorbidity. Physical activity was a protective factor in both age groups and smoking a risk factor for the ‘respiratory-mental-articular’.ConclusionMultimorbidity is common worldwide, especially in HICs and Russia. Health policies in each country addressing coordination and support are needed to face the complexity of a pattern of growing multimorbidity.

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Estimates and Determinants of SARS-Cov-2 Seroprevalence and Infection Fatality Ratio Using Latent Class Analysis: The Population-Based Tirschenreuth Study in the Hardest-Hit German County in Spring 2020

Viruses ◽

10.3390/v13061118 ◽

2021 ◽

Vol 13 (6) ◽

pp. 1118

Author(s):

Ralf Wagner ◽

David Peterhoff ◽

Stephanie Beileke ◽

Felix Günther ◽

Melanie Berr ◽

...

Keyword(s):

Latent Class Analysis ◽

Latent Class ◽

Care Home ◽

Case Fatality ◽

The Elderly ◽

Population Based ◽

Class Analysis ◽

Population Based Study ◽

Targeted Testing ◽

June July

SARS-CoV-2 infection fatality ratios (IFR) remain controversially discussed with implications for political measures. The German county of Tirschenreuth suffered a severe SARS-CoV-2 outbreak in spring 2020, with particularly high case fatality ratio (CFR). To estimate seroprevalence, underreported infections, and IFR for the Tirschenreuth population aged ≥14 years in June/July 2020, we conducted a population-based study including home visits for the elderly, and analyzed 4203 participants for SARS-CoV-2 antibodies via three antibody tests. Latent class analysis yielded 8.6% standardized county-wide seroprevalence, a factor of underreported infections of 5.0, and 2.5% overall IFR. Seroprevalence was two-fold higher among medical workers and one third among current smokers with similar proportions of registered infections. While seroprevalence did not show an age-trend, the factor of underreported infections was 12.2 in the young versus 1.7 for ≥85-year-old. Age-specific IFRs were <0.5% below 60 years of age, 1.0% for age 60–69, and 13.2% for age 70+. Senior care homes accounted for 45% of COVID-19-related deaths, reflected by an IFR of 7.5% among individuals aged 70+ and an overall IFR of 1.4% when excluding senior care home residents from our computation. Our data underscore senior care home infections as key determinant of IFR additionally to age, insufficient targeted testing in the young, and the need for further investigations on behavioral or molecular causes of the fewer infections among current smokers.

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Latent class analysis of the Apathy Scale does not identify subtypes of apathy in general population-based older persons

International Journal of Geriatric Psychiatry ◽

10.1002/gps.4413 ◽

2016 ◽

Vol 31 (9) ◽

pp. 1021-1028 ◽

Cited By ~ 2

Author(s):

Isis Groeneweg-Koolhoven ◽

Lotte J. Huitema ◽

Margot W. M. de Waal ◽

Max L. Stek ◽

Jacobijn Gussekloo ◽

...

Keyword(s):

General Population ◽

Latent Class Analysis ◽

Older Persons ◽

Latent Class ◽

Population Based ◽

Class Analysis

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Latent class analysis identifies three subtypes of aggressive end-of-life care: A population-based study in Taiwan

European Journal of Cancer ◽

10.1016/j.ejca.2013.05.005 ◽

2013 ◽

Vol 49 (15) ◽

pp. 3284-3291 ◽

Cited By ~ 4

Author(s):

Mei-Ling Chen ◽

Yun-Yi Chen ◽

Siew Tzuh Tang

Keyword(s):

Latent Class Analysis ◽

End Of Life ◽

End Of Life Care ◽

Latent Class ◽

Population Based ◽

Class Analysis ◽

Life Care ◽

Population Based Study

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Health Information-Seeking Behaviors of a German Speaking Minority in Italy: Latent Class Analysis of a Population-Based Cross-Sectional Survey

10.21203/rs.3.rs-483915/v2 ◽

2021 ◽

Author(s):

Dietmar Ausserhofer ◽

Wolfgang Wiedermann ◽

Christian J. Wiedermann ◽

Ulrich Becker ◽

Anna Vögele ◽

...

Keyword(s):

Latent Class Analysis ◽

Health Information ◽

Information Seeking ◽

Latent Class ◽

Population Based ◽

Health Information Seeking ◽

Class Analysis ◽

Online Class ◽

German Speaking ◽

Information Seeking Behaviors

Abstract Latent classes of health information-seeking behaviors of adults in a German-speaking minority of Italy were explored in a population-based, telephone survey on 10 health information sources conducted in South Tyrol, Italy. Data were collected from 504 adults (primary language German 68%, Italian 28%) and analyzed using latent class analysis and latent class multinomial logistic regression models. Three classes of health information-seeking behaviors emerged: “multidimensional” (23.3%), “interpersonal” (38.6%) and “technical/online” (38.1%). Compared to the “technical/online” class, “interpersonal” class members were older, had lower education than high school, and were less likely to be of Italian ethnicity. “Multidimensional” class members were more likely to be female, older, and of German ethnicity than those in the “technical/online” class. Linguistic ethnicity explains membership in classes of health-information-seeking behaviour. Policy makers and healthcare providers need to consider the health information-seeking behaviors of population subgroups to promote the health literacy skills of language minority groups.

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Intelligence and neuroticism in relation to depression and psychological distress: Evidence from two large population cohorts

European Psychiatry ◽

10.1016/j.eurpsy.2016.12.012 ◽

2017 ◽

Vol 43 ◽

pp. 58-65 ◽

Cited By ~ 15

Author(s):

L.B. Navrady ◽

S.J. Ritchie ◽

S.W.Y. Chan ◽

D.M. Kerr ◽

M.J. Adams ◽

...

Keyword(s):

Psychological Distress ◽

Protective Factor ◽

Short Form ◽

Large Population ◽

Family Health ◽

Population Based ◽

Health Study ◽

Increased Risk ◽

Ability Tests ◽

Risk For Depression

AbstractBackground:Neuroticism is a risk factor for selected mental and physical illnesses and is inversely associated with intelligence. Intelligence appears to interact with neuroticism and mitigate its detrimental effects on physical health and mortality. However, the inter-relationships of neuroticism and intelligence for major depressive disorder (MDD) and psychological distress has not been well examined.Methods:Associations and interactions between neuroticism and general intelligence (g) on MDD, self-reported depression, and psychological distress were examined in two population-based cohorts: Generation Scotland: Scottish Family Health Study (GS:SFHS, n = 19,200) and UK Biobank (n = 90,529). The Eysenck Personality Scale Short Form-Revised measured neuroticism and g was extracted from multiple cognitive ability tests in each cohort. Family structure was adjusted for in GS:SFHS.Results:Neuroticism was strongly associated with increased risk for depression and higher psychological distress in both samples. Although intelligence conferred no consistent independent effects on depression, it did increase the risk for depression across samples once neuroticism was adjusted for. Results suggest that higher intelligence may ameliorate the association between neuroticism and self-reported depression although no significant interaction was found for clinical MDD. Intelligence was inversely associated with psychological distress across cohorts. A small interaction was found across samples such that lower psychological distress associates with higher intelligence and lower neuroticism, although effect sizes were small.Conclusions:From two large cohort studies, our findings suggest intelligence acts a protective factor in mitigating the effects of neuroticism on psychological distress. Intelligence does not confer protection against diagnosis of depression in those high in neuroticism.

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Who Should Be Targeted for the Prevention of Birth Defects? A Latent Class Analysis Based on a Large, Population-Based, Cross-Sectional Study in Shaanxi Province, Western China

PLoS ONE ◽

10.1371/journal.pone.0155587 ◽

2016 ◽

Vol 11 (5) ◽

pp. e0155587 ◽

Cited By ~ 2

Author(s):

Zhonghai Zhu ◽

Yue Cheng ◽

Wenfang Yang ◽

Danyang Li ◽

Xue Yang ◽

...

Keyword(s):

Latent Class Analysis ◽

Birth Defects ◽

Latent Class ◽

Large Population ◽

Population Based ◽

Cross Sectional Study ◽

Shaanxi Province ◽

Western China ◽

Sectional Study ◽

Cross Sectional

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Heterogeneity in quality of life of long‐term colon cancer survivors: a latent class analysis of the population‐based PROFILES registry

The Oncologist ◽

10.1002/onco.13655 ◽

2020 ◽

Author(s):

Felix J. Clouth ◽

Arturo Moncada‐Torres ◽

Gijs Geleijnse ◽

Floortje Mols ◽

Felice N. Erning ◽

...

Keyword(s):

Quality Of Life ◽

Colon Cancer ◽

Cancer Survivors ◽

Latent Class Analysis ◽

Latent Class ◽

Population Based ◽

Class Analysis

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Social position and anthropometric status among adults in the ELSA-Brasil study: a latent class analysis

Cadernos de Saúde Pública ◽

10.1590/0102-311x00168918 ◽

2021 ◽

Vol 37 (9) ◽

Author(s):

Sheila Maria Alvim Matos ◽

Leila Denise Alves Ferreira Amorim ◽

Francisco José Gondim Pitanga ◽

Ana Luísa Patrão ◽

Sandhi M. Barreto ◽

...

Keyword(s):

Latent Class Analysis ◽

Latent Variables ◽

Skin Color ◽

Latent Class ◽

Multivariate Logistic Regression Analysis ◽

Social Position ◽

Adult Health ◽

Class Analysis ◽

Cross Sectional ◽

Anthropometric Status

Abstract: The objective of the present study was to evaluate the association between social position and anthropometric status in women and men Brazilian adult. This was a cross-sectional study that used baseline data collected from 2008 to 2010 for the Brazilian Longitudinal Study of Adult Health (ELSA-Brasil, in Portuguese), in the six major Brazilian state capital cities. A total of 15,105 active and retired civil servants aged from 35 to 74 years. Two latent variables were defined by latent class analysis, social position and anthropometric status. Both constructs and the analyses were separately evaluated by sex. Associations were assessed using multivariate logistic regression analysis with adjustment for age, self-reported skin color/race, and marital status. Around 44% of the women and 26% of the men were classified as overweight or obese. Social position tended to be lower in women (43.2%) and higher among men (40.4%). Heavier women were more likely to be black and brown-skinned, whereas slimmer women were more likely to be white. After adjustment, women’s weight increased as social position decreased (OR = 1.52; 95%CI: 1.36-1.70), whereas in men weight decreased as social position decreased (OR = 0.87; 95%CI: 0.76-0.99). Social position affected the anthropometric status of women and men differently, with body patterns also being affected by ethnicity/skin color, showing the potentiality of taking the intersectional perspective when investigating the possible social determinants of the phenomenon.

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Using Latent Class Analysis to Identify Health Lifestyle Profiles and Their Association with Suicidality among Adolescents in Benin

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18168602 ◽

2021 ◽

Vol 18 (16) ◽

pp. 8602

Author(s):

Fanny Hoogstoel ◽

Lucresse Corine Fassinou ◽

Sékou Samadoulougou ◽

Céline Mahieu ◽

Yves Coppieters ◽

...

Keyword(s):

Psychological Distress ◽

Latent Class Analysis ◽

Parental Support ◽

Latent Class ◽

Physical Violence ◽

Prevalence Ratio ◽

Health Risk Behaviors ◽

Class Analysis ◽

Health Lifestyle ◽

Increased Risk

Youth suicidality is considerably prevalent in low- and middle-income countries, including Benin. Factors such as psychosocial distress, socio-environmental factors, and health risk behaviors are associated with suicidality. However, little is known about how these factors co-occur in these countries. An analysis of these factors taken together would help to identify the profiles most at risk and better target prevention policies. Our study aimed to identify profiles related to these factors and their association with suicidality among adolescents in Benin. Data from the 2016 Global School-Based Student Health Survey were used, and factors related to lifestyle (tobacco and alcohol consumption and physical activity), physical violence, parental support, and psychological distress were studied. Latent class analysis was used to identify the profiles, and a modified Poisson regression with generalized estimating equations, adjusted for sociodemographic characteristics, was performed to assess the association between these profiles and suicidality. The survey results show that globally, 13.8% of the adolescents (n = 2536) aged 11 to 18 had thought about suicide, 15.6% had planned suicide, and 15.6% had attempted suicide. Four profiles were identified: a low-risk group, one with psychological distress problems, a group with violence problems, and one with alcohol, tobacco, and violence problems. The risk of suicidality, in terms of ideation, planning, or attempting, was higher for adolescents in Profiles 2, 3, and 4 than those in Profile 1 (p < 0.05). Adolescents in Profile 2 were particularly affected by this increased risk (prevalence ratio (PR) for ideation = 1.13, 95% CI = 1.03–1.23; PR for planning = 1.12, 95% CI = 1.04–1.22; PR for attempting = 1.09, 95% CI = 1.01–1.17). This study highlights the typical profiles that may be linked with suicidality among adolescents in Benin. A holistic consideration of these factors could help in planning better preventive measures to reduce suicidality among adolescents in Benin.

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