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Abstract Background Optimal blood pressure (BP) levels to reduce the long-term risk of cognitive decline remains controversial. We aimed to investigate the association between BP and anti-hypertensive treatment status with cognitive decline in older adults. Methods This study used data from the China Health and Retirement Longitudinal Study. Cognitive function was assessed at year 2011, 2013, 2015, and 2018. Global cognitive Z-score was calculated as the average score of episodic memory and mental intactness. BP were measured at the first and second wave. Pulse pressure (PP) was calculated as systolic BP (SBP) minus diastolic BP. Cumulative BP was calculated as the area under the curve using BP measurements from 2011 to 2013. Linear mixed models were used to assess the longitudinal association between BP-related measurements and cognitive decline. Results We included 11,671 participants (47.3% men and mean age 58.6 years). Individual with BP > 140/90 mm Hg or taking anti-hypertensive medication were independently associated with accelerated cognitive decline (β=-0.014, 95% CI: -0.020 to -0.007). Individuals with anti-hypertensive medication use, but with controlled SBP to less than 120 mm Hg did not have a significantly increased risk of cognitive decline compared with normotension (β=-0.003, 95% CI: -0.021 to 0.014). Individuals on anti-hypertensive treatment with PP of more than 70 mm Hg had a significantly higher risk of cognitive decline (β=-0.033, 95% CI: -0.045 to -0.020). Regardless of anti-hypertensive treatment status, both elevated baseline and cumulative SBP and PP were found to be independently associated with accelerated cognitive decline. Conclusions Cumulatively elevated SBP, PP and uncontrolled BP were associated with subsequent cognitive decline. Effectively controlling BP with anti-hypertensive treatment may be able to preserve cognitive decline in older adults.

Abstract Background Dementia is defined as a cognitive decline that affects functional status. Longitudinal ageing surveys often lack a clinical diagnosis of dementia though measure cognition and daily function over time. We used unsupervised machine learning and longitudinal data to identify transition to probable dementia. Methods Multiple Factor Analysis was applied to longitudinal function and cognitive data of 15,278 baseline participants (aged 50 years and more) from the Survey of Health, Ageing, and Retirement in Europe (SHARE) (waves 1, 2 and 4–7, between 2004 and 2017). Hierarchical Clustering on Principal Components discriminated three clusters at each wave. We estimated probable or “Likely Dementia” prevalence by sex and age, and assessed whether dementia risk factors increased the risk of being assigned probable dementia status using multistate models. Next, we compared the “Likely Dementia” cluster with self-reported dementia status and replicated our findings in the English Longitudinal Study of Ageing (ELSA) cohort (waves 1–9, between 2002 and 2019, 7840 participants at baseline). Results Our algorithm identified a higher number of probable dementia cases compared with self-reported cases and showed good discriminative power across all waves (AUC ranged from 0.754 [0.722–0.787] to 0.830 [0.800–0.861]). “Likely Dementia” status was more prevalent in older people, displayed a 2:1 female/male ratio, and was associated with nine factors that increased risk of transition to dementia: low education, hearing loss, hypertension, drinking, smoking, depression, social isolation, physical inactivity, diabetes, and obesity. Results were replicated in ELSA cohort with good accuracy. Conclusions Machine learning clustering can be used to study dementia determinants and outcomes in longitudinal population ageing surveys in which dementia clinical diagnosis is lacking.

Abstract Background Population-based surveys are the main data source to generate health-related indicators required to monitor progress toward national, regional and global goals effectively. Although the Eastern Mediterranean Region of World Health Organization (WHO) member states conduct many population-based surveys, they are not led regularly and fail to provide relevant indicators appropriately. Therefore, this study aims two-fold: to map out population-based surveys to be conducted data for the health-related indicators in the Region and propose a timetable for conducting national population-based surveys in the Region. Methods The study was conducted in six phases: 1) Selecting survey-based indicators; 2) Extracting and comparing relevant survey modules; 3) Identifying sources of data for the indicators; 4) Assessing countries' status in reporting on core health indicators; 5) Review and confirmation of the results by the experts. Results Population-based surveys are the sources of data for 44 (65%) out of 68 regional core health indicators and two (18%) out of 11 health-related Sustainable Development Goals (SDG) 3 indicators. The Health Examination Survey (HES) could cover 65% of the survey-based indicators. A total of 91% of survey-based indicators are obtained by a combination of HES, Demographic and Health Survey (DHS), Multiple Indicator Cluster Survey (MICS) and Global School-based Student Health Survey (GSHS). Conclusion In order to effectively report health-related indicators, HES, DHS/MICS and GSHS are considered essential in national survey timetables. Each country needs to devise and implement a plan for population-based surveys by considering factors such as national health priorities, financial and human capacities, and previous experiences.

Abstract Background Termination of pregnancy (TOP) is a common cause of maternal morbidity and mortality in low- and middle-income countries. Population-based surveys are the major data source for TOP data in LMICs but are known to have shortcomings that require improving. The EN-INDEPTH multi-country survey employed a full pregnancy history approach with roster and new questions on TOP and Menstrual Restoration. This mixed methods paper assesses the completeness of responses to questions eliciting TOP information from respondents and reports on practices, barriers, and facilitators to TOP reporting. Methods The EN-INDEPTH study was a population-based cross-sectional study. The Full Pregnancy History arm of the study surveyed 34,371 women of reproductive age between 2017 and 2018 in five Health and Demographic Surveillance System (HDSS) sites of the INDEPTH network: Bandim, Guinea-Bissau; Dabat, Ethiopia; IgangaMayuge, Uganda; Kintampo, Ghana; and Matlab, Bangladesh. Completeness and time spent in answering TOP questions were evaluated using simple tabulations and summary statistics. Exact binomial 95% confidence intervals were computed for TOP rates and ratios. Twenty-eight (28) focus group discussions were undertaken and analysed thematically. Results Completeness of responses regarding TOP was between 90.3 and 100.0% for all question types. The new questions elicited between 2.0% (1.0–3.4), 15.5% (13.9–17.3), and 11.5% (8.8–14.7) lifetime TOP cases over the roster questions from Dabat, Ethiopia; Matlab, Bangladesh; and Kintampo, Ghana, respectively. The median response time on the roster TOP questions was below 1.3 minutes in all sites. Qualitative results revealed that TOP was frequently stigmatised and perceived as immoral, inhumane, and shameful. Hence, it was kept secret rendering it difficult and uncomfortable to report. Miscarriages were perceived to be natural, being easier to report than TOP. Interviewer techniques, which were perceived to facilitate TOP disclosure, included cultural competence, knowledge of contextually appropriate terms for TOP, adaptation to interviewee’s individual circumstances, being non-judgmental, speaking a common language, and providing detailed informed consent. Conclusions Survey roster questions may under-represent true TOP rates, since the new questions elicited responses from women who had not disclosed TOP in the roster questions. Further research is recommended particularly into standardised training and approaches to improving interview context and techniques to facilitate TOP reporting in surveys.