Statistical methods for causal analysis in life course research: an illustration of a cross-lagged structural equation model, a latent growth model, and an autoregressive latent trajectories model

We present three statistical methods for causal analysis in life course research that are able to take into account the order of events and their possible causal relationship: a cross-lagged model, a latent growth model (LGM), and a synthesis of the two, an autoregressive latent trajectories model (ALT). We apply them to a highly relevant causality question in life course and health inequality research: does socioeconomic status (SES) affect health (social causation) or does health affect SES (health selection)? Using retrospective survey data from SHARELIFE covering life courses from childhood to old age, the cross-lagged model suggests an equal importance of social causation and health selection; the LGM stresses the effect of education on health growth; whereas the ALT model confirms no causality. We discuss examples, present short and non-technical introduction of each method, and illustrate them by highlighting their relative strengths for causal life course analysis

The long arm of childhood circumstances on health in old age: Evidence from SHARELIFE

Socioeconomic status (SES) and health during childhood have been consistently observed to be associated with health in old age in many studies. However, the exact mechanisms behind these two associations have not yet been fully understood. The key challenge is to understand how childhood SES and health are associated. Furthermore, data on childhood factors and life course mediators are sometimes unavailable, limiting potential analyses. Using SHARELIFE data (N = 17230) we measure childhood SES and health circumstances, and examine their associations with old age health and their possible pathways via education, adult SES, behavioural risks, and labour market deprivation. We employ structural equation modelling to examine the mechanism of the long lasting impact of childhood SES and health on later life health, and how mediators partly contribute to these associations. The results show that childhood SES is substantially associated with old age health, albeit almost fully mediated by education and adult SES. Childhood health and behavioural risks have a strong effect on old age health, but they do not mediate the association between childhood SES and old age health. Childhood health in contrast retains a strong association with old age health after taking adulthood characteristics into account. This paper discusses the notion of the ‘long arm of childhood’ and concludes that it is a lengthy, mediated, incremental progression rather than a direct effect. Policies should certainly focus on childhood, especially when it comes to addressing childhood health conditions, but our results suggest other important entry points for improving old age health when it comes to socioeconomic determinants

What causes health inequality? : a systematic review on the relative importance of social causation and health selection

First published online 18 June 2015. The social gradient in health is one of the most reliable findings in public health research. The two competing hypotheses that try to explain this gradient are known as the social causation and the health selection hypothesis. There is currently no synthesis of the results of studies that test both hypotheses. We provide a systematic review of the literature that has addressed both the health selection and social causation hypotheses between 1994 and 2013 using seven databases following PRISMA rules. The search strategy resulted in 2952 studies, of which, we included 34 in the review. The synthesis of these studies suggests that there is no general preference for either of the hypotheses (12 studies for social causation, 10 for health selection). However, both a narrative synthesis as well as meta-regression results show that studies using indicators for socio-economic status (SES) that are closely related to the labor market find equal support for health selection and social causation, whereas indicators of SES like education and income yield results that are in favor of the social causation hypothesis. High standards in statistical modeling were associated with more support for health selection. The review highlights the fact that the causal mechanisms behind health inequalities are dependent on whether or not the dimension being analyzed closely reflects labor market success. Additionally, further research should strive to improve the statistical modeling of causality, as this might influence the conclusions drawn regarding the relative importance of health selection and social causation

The recent secular trend in grip strength among older adults: findings from the English Longitudinal Study of Ageing

Purpose: Weaker grip strength in older adults is associated with adverse health outcomes and is a key component of sarcopenia. The secular trend of grip strength is, therefore, relevant in the setting of ageing populations. A recent study suggested differences in this trend among countries in mainland Europe. We used data from the English Longitudinal Study of Ageing (ELSA) to investigate the recent secular trend of older English adults. Methods: We used data on participants aged 50–89 having their first measurement of grip strength in waves 2 (2002/2003), 4 (2008/2009) or 6 (2012/2013) of ELSA. Grip was measured using a Smedley dynamometer. We expressed grip values as Z-scores (number of standard deviations above the age and gender mean from normative data) for use in linear regression analyses examining the annual secular trend after adjustment for potential confounders. Results: We included a total of 11,476 participants from the three waves of ELSA. Grip strength declined across the three waves, with mean (SD) Z-scores of 0.01 (0.94), − 0.06 (0.97) and − 0.20 (0.98) in waves 2, 4 and 6, respectively. The annual Z-score decline after adjustments was 0.03 SDs (95% CI 0.02, 0.03) per year. Conclusion: We saw evidence of a recent slight decline in the grip strength of older English adults. Over the 9-year period of this study, the decline seen is equivalent to 65-year-olds’ mean strength declining to that previously seen in individuals at age 69. Further monitoring of secular trends in grip strength and investigation of possible causes are warranted

Patterns of homelessness and housing instability and the relationship with mental health disorders among young people transitioning from out-of-home care: Retrospective cohort study using linked administrative data

Objectives: The study examined the relationship between mental health, homelessness and housing instability among young people aged 15–18 years old who transitioned from out-of-home in 2013 to 2014 in the state of Victoria, Australia with follow-up to 2018. We determined the various mental health disorders and other predictors that were associated with different levels of homelessness risk, including identifying the impact of dual diagnosis of mental health and substance use disorder on homelessness. Methodology: Using retrospective de-identified linked administrative data from various government departments we identified various dimensions of homelessness which were mapped from the European Topology of Homelessness (ETHOS) framework and associated mental health variables which were determined from the WHO ICD-10 codes. We used ordered logistic regression and Poisson regression analysis to estimate the impact of homelessness and housing instability respectively. Results: A total homelessness prevalence of 60% was determined in the care-leaving population. After adjustment, high risk of homelessness was associated with dual diagnosis of mental health and substance use disorder, intentional self-harm, anxiety, psychotic disorders, assault and maltreatment, history of involvement with the justice system, substance use prior to leaving care, residential and home-based OHC placement and a history of staying in public housing. Conclusions: There is clearly a need for policy makers and service providers to work together to find effective housing pathways and integrated health services for this heterogeneous group of vulnerable young people with complex health and social needs. Future research should determine longitudinally the bidirectional relationship between mental health disorders and homelessness

Teacher Absenteeism and Remote Area Allowance Baseline Survey

Tim peneliti koordinator penelitian: nina toyamah peneliti inti dan koordinator lapangan: nina toyamah, bambang sulaksono, meuthia rosfadhila, silvia devina, sirojuddin arif, stella aleida hutagalung, lisna sulinar sari, andriani, upik sabainingrum, nur aini peneliti lokal: bandung dan sukabumi, Jawa Barat ruhmaniyati dan dudi lesmanasurakarta, Jawa Tengah pratidina rupajati dan dwi bambang s.tuban, Jawa Timur rico feryanto dan devy pharma christianpekanbaru, Riau susy edwina dan evy maharanilahat, sumatra selatan diana handayani dan endy setiawan lombok tengah, Nusa Tenggara Barat eri hidayati dan nurul hidayatigowa, Sulawesi Selatan awaluddin dan titi nuriatinunukan, Kalimantan Timur masruni dan merry tobingkolaka, Sulawesi Tenggara abdi dan nurjana penanggung jawab dan penasihat penelitian: asep suryahadi editor valentina yulita dyah utari abstrak survei baseline kehadiran guru 2008 bertujuan untuk memperoleh perkiraan terbaru tingkat absensi guru di sekolah dasar (sd), mengetahui Perubahannya dalam lima tahun terakhir sejak diadakannya survei pertama pada 2003, dan mengetahui pengaruh pemberian program bantuan kesejahteraan untuk guru di daerah terpencil (bankes) terhadap tingkat absensi guru di Indonesia. selain itu, survei ini juga menggali informasi tentang tingkat absensi murid sd dan kemampuan murid kelas iv dalam pelajaran matematika dan bahasa Indonesia. survei dilaksanakan di lima kabupaten penerima bankes dan lima kabupaten/kota nonpenerima bankes yang tersebar di sembilan provinsi di Indonesia. jumlah total sdn sampel adalah 39 sdn penerima bankes dan 131 sdn nonpenerima bankes. survei menunjukkan bahwa meskipun tingkat absensi guru di Indonesia selama lima tahun terakhir cenderung menurun, variasi tingkat absensi guru antardaerah sampel yang sama meningkat. survei 2008 ini juga memperlihatkan bahwa keterpencilan wilayah sangat memengaruhi tingkat absensi guru. tingkat absensi guru di daerah-daerah yang relatif lebih maju atau perkotaan lebih rendah daripada tingkat absensi guru di perdesaan/kabupaten. selain itu, tingkat absensi guru di kabupaten/kota di wilayah barat Indonesia lebih rendah daripada tingkat absensi guru di wilayah tengah/timur Indonesia. pola yang sama tampak pada tingkat absensi murid dan hasil tes matematika dan bahasa Indonesia para murid. tingkat absensi guru dan murid berkorelasi negatif terhadap hasil tes matematika dan bahasa Indonesia murid kelas iv. berkaitan dengan program bankes, pemberian dana bankes bagi para guru di daerah terpencil–yang antara lain bertujuan menurunkan tingkat absensi guru di sekolah–belum menunjukkan dampak nyata. secara umum tingkat absensi guru di wilayah penerima bankes masih lebih tinggi daripada tingkat absensi guru di wilayah nonpenerima bankes. indikasi dampak pemberian bankes terhadap tingkat absensi guru hanya terlihat di kabupaten sukabumi dan kabupaten lahat. kata kunci: absensi, bantuan kesejahteraan (bankes), daerah terpencil, gur

Understanding COVID-19 vaccine hesitancy: A cross-sectional study in Malang District, Indonesia

Introduction: Vaccine hesitancy could undermine efforts to reduce incidence of coronavirus disease 2019 (COVID-19). Understanding COVID-19 vaccine hesitancy is crucial to tailoring strategies to increase vaccination acceptance. This study aims to investigate the prevalence of and the reasons for COVID-19 vaccine hesitancy in Malang District, Indonesia. Methods: Data come from a cross-sectional study among individuals aged 17-85 years old (N = 3,014). Multivariate ordered logistic regression was used to identify factors associated with postponing or refusing COVID-19 vaccines. The Oxford COVID-19 vaccine hesitancy scale was used to measure vaccine hesitancy. A wide range of reasons for hesitancy, including coronavirus vaccine confidence and complacency, vaccination knowledge, trust and attitude in health workers and health providers, coronavirus conspiracy, anger reaction and need for chaos, populist views, lifestyle, and religious influence, was examined. Results and discussion: The results show that 60.2% of the respondents were hesitant to receive the COVID-19 vaccine. Low confidence and complacency beliefs about the vaccine (OR = 1.229, 95% CI = 1.195–1.264) and more general sources of mistrust within the community, particularly regarding health providers (OR = 1.064, 95% CI = 1.026–1.102) and vaccine developers (OR = 1.054, 95% CI = 1.027–1.082), are associated with higher levels of COVID-19 vaccine hesitancy. Vaccine hesitancy is also associated with anger reactions (OR = 1.019, 95% CI = 0.998–1.040), need for chaos (OR = 1.044, 95% CI = 1.022–1.067), and populist views (OR = 1.028, 95% CI = 1.00–1.056). The findings were adjusted for socio-demographic factors, including age, sex, education, marital status, working status, type of family, household income, religious beliefs, and residency. The results suggest the need for an effective health promotion program to improve community knowledge of the COVID-19 vaccine, while effective strategies to tackle “infodemics” are needed to address hesitancy during a new vaccine introduction program

P284 Evaluation of a self-management smartphone app for those living with Sjögren’s syndrome: a fully remote randomised pilot and feasibility trial

Background/Aims People with Sjögren's Syndrome (SS) experience a range of symptoms, including dryness, pain, fatigue, and poor sleep. Pharmacological management is limited, and SS patients may not have timely access to non-pharmacological support with these symptoms. Accessible evidence-based support via an app may benefit some. An evidence-based app (Sjogo) was co-developed with SS patients through a series of focus groups and workshops (n = 7). Alongside the workshops, behaviour change techniques and evidence-based intervention components were identified from the literature and known evidence-based interventions and were discussed with participants in focus groups. An app was developed containing active ingredients (e.g. features supporting behaviour change, validation of experiences, reflective activity diary, goal setting, cognitive behaviour therapy for sleep) to facilitate participation in daily activities and support symptom management. An additional control app was developed which contained “information only” content. We conducted a fully remote pilot feasibility RCT of the app. The aim of the study was to test trial procedures including recruitment rates, outcome completion, and engagement with the app. Methods The Sjogo app was released internationally for 8 weeks on Android and iOS app stores in January 2021. Potential participants were alerted to the trial through social media and patient groups. Those who downloaded the app were guided through in-app study procedures (screening, informed consent, demographic questions and baseline symptom, patient activation and quality of life outcome completion). Outcome measures included ESSPRI, Modified Fatigue Impact Scale, depression (VAS), anxiety (VAS), Sleep Condition Index, PAM-10 and ICECAP-A. Participants were randomised to an information-version (control) or full-version of Sjogo containing features supporting behaviour change. Users could engage with Sjogo as they wished and were asked to complete outcomes at baseline, 5 and 10 weeks. Results 996 participants from 33 countries downloaded Sjogo, with 617 (61.95%) completing the onboarding procedures and consenting to participate in the study. These participants were randomised to the full-version of the app (n = 318) or control-version (n = 299). Participants were mostly female (95.62%) iOS users (55.11%) from the UK (54.62%) or USA (28.92%) with a mean age of 50.97 (SD 13.75). Outcome completion rates at 5 and 10 weeks were 29.24% and 13.52% respectively for the full-version and 44.48% and 28.42% for the control-version. Conclusion Completion rates demonstrate that Sjogo can be evaluated in a real-world context in a fully powered RCT with large numbers of participants over a short timescale. However, maintaining engagement rates is challenging. App design could be optimised to maintain effective engagement with the app and support behaviour change. A process evaluation which includes further analysis of app engagement data and interviews with participants will further inform improvements to app content, features and trial procedures

Prediction of dementia risk in low-income and middle-income countries (the 10/66 Study): an independent external validation of existing models

BackgroundTo date, dementia prediction models have been exclusively developed and tested in high-income countries (HICs). However, most people with dementia live in low-income and middle-income countries (LMICs), where dementia risk prediction research is almost non-existent and the ability of current models to predict dementia is unknown. This study investigated whether dementia prediction models developed in HICs are applicable to LMICs.MethodsData were from the 10/66 Study. Individuals aged 65 years or older and without dementia at baseline were selected from China, Cuba, the Dominican Republic, Mexico, Peru, Puerto Rico, and Venezuela. Dementia incidence was assessed over 3–5 years, with diagnosis according to the 10/66 Study diagnostic algorithm. Discrimination and calibration were tested for five models: the Cardiovascular Risk Factors, Aging and Dementia risk score (CAIDE); the Study on Aging, Cognition and Dementia (AgeCoDe) model; the Australian National University Alzheimer's Disease Risk Index (ANU-ADRI); the Brief Dementia Screening Indicator (BDSI); and the Rotterdam Study Basic Dementia Risk Model (BDRM). Models were tested with use of Cox regression. The discriminative accuracy of each model was assessed using Harrell's concordance (c)-statistic, with a value of 0·70 or higher considered to indicate acceptable discriminative ability. Calibration (model fit) was assessed statistically using the Grønnesby and Borgan test.Findings11 143 individuals without baseline dementia and with available follow-up data were included in the analysis. During follow-up (mean 3·8 years [SD 1·3]), 1069 people progressed to dementia across all sites (incidence rate 24·9 cases per 1000 person-years). Performance of the models varied. Across countries, the discriminative ability of the CAIDE (0·52≤c≤0·63) and AgeCoDe (0·57≤c≤0·74) models was poor. By contrast, the ANU-ADRI (0·66≤c≤0·78), BDSI (0·62≤c≤0·78), and BDRM (0·66≤c≤0·78) models showed similar levels of discriminative ability to those of the development cohorts. All models showed good calibration, especially at low and intermediate levels of predicted risk. The models validated best in Peru and poorest in the Dominican Republic and China.InterpretationNot all dementia prediction models developed in HICs can be simply extrapolated to LMICs. Further work defining what number and which combination of risk variables works best for predicting risk of dementia in LMICs is needed. However, models that transport well could be used immediately for dementia prevention research and targeted risk reduction in LMICs