METHODS: Between 2009 and 2012, a kilometre-long walk was completed by trained investigators in 462 communities across 16 countries to collect data on tobacco marketing. We interviewed community members about their exposure to traditional and non-traditional marketing in the previous six months. To examine differences in marketing between urban and rural communities and between high-, middle- and low-income countries, we used multilevel regression models controlling for potential confounders.
FINDINGS: Compared with high-income countries, the number of tobacco advertisements observed was 81 times higher in low-income countries (incidence rate ratio, IRR: 80.98; 95% confidence interval, CI: 4.15-1578.42) and the number of tobacco outlets was 2.5 times higher in both low- and lower-middle-income countries (IRR: 2.58; 95% CI: 1.17-5.67 and IRR: 2.52; CI: 1.23-5.17, respectively). Of the 11,842 interviewees, 1184 (10%) reported seeing at least five types of tobacco marketing. Self-reported exposure to at least one type of traditional marketing was 10 times higher in low-income countries than in high-income countries (odds ratio, OR: 9.77; 95% CI: 1.24-76.77). For almost all measures, marketing exposure was significantly lower in the rural communities than in the urban communities.
CONCLUSION: Despite global legislation to limit tobacco marketing, it appears ubiquitous. The frequency and type of tobacco marketing varies on the national level by income group and by community type, appearing to be greatest in low-income countries and urban communities.
Objective: To examine whether the associations of fish consumption with risk of CVD or of mortality differ between individuals with and individuals without vascular disease.
Design, Setting, and Participants: This pooled analysis of individual participant data involved 191 558 individuals from 4 cohort studies-147 645 individuals (139 827 without CVD and 7818 with CVD) from 21 countries in the Prospective Urban Rural Epidemiology (PURE) study and 43 413 patients with vascular disease in 3 prospective studies from 40 countries. Adjusted hazard ratios (HRs) were calculated by multilevel Cox regression separately within each study and then pooled using random-effects meta-analysis. This analysis was conducted from January to June 2020.
Exposures: Fish consumption was recorded using validated food frequency questionnaires. In 1 of the cohorts with vascular disease, a separate qualitative food frequency questionnaire was used to assess intake of individual types of fish.
Main Outcomes and Measures: Mortality and major CVD events (including myocardial infarction, stroke, congestive heart failure, or sudden death).
Results: Overall, 191 558 participants with a mean (SD) age of 54.1 (8.0) years (91 666 [47.9%] male) were included in the present analysis. During 9.1 years of follow-up in PURE, compared with little or no fish intake (≤50 g/mo), an intake of 350 g/wk or more was not associated with risk of major CVD (HR, 0.95; 95% CI, 0.86-1.04) or total mortality (HR, 0.96; 0.88-1.05). By contrast, in the 3 cohorts of patients with vascular disease, the HR for risk of major CVD (HR, 0.84; 95% CI, 0.73-0.96) and total mortality (HR, 0.82; 95% CI, 0.74-0.91) was lowest with intakes of at least 175 g/wk (or approximately 2 servings/wk) compared with 50 g/mo or lower, with no further apparent decrease in HR with consumption of 350 g/wk or higher. Fish with higher amounts of ω-3 fatty acids were strongly associated with a lower risk of CVD (HR, 0.94; 95% CI, 0.92-0.97 per 5-g increment of intake), whereas other fish were neutral (collected in 1 cohort of patients with vascular disease). The association between fish intake and each outcome varied by CVD status, with a lower risk found among patients with vascular disease but not in general populations (for major CVD, I2 = 82.6 [P = .02]; for death, I2 = 90.8 [P = .001]).
Conclusions and Relevance: Findings of this pooled analysis of 4 cohort studies indicated that a minimal fish intake of 175 g (approximately 2 servings) weekly is associated with lower risk of major CVD and mortality among patients with prior CVD but not in general populations. The consumption of fish (especially oily fish) should be evaluated in randomized trials of clinical outcomes among people with vascular disease.
METHODS: Between August 2020 and September 2021, we surveyed 24,506 community-dwelling participants from the Prospective Urban-Rural Epidemiology (PURE) study across high (HIC), upper middle (UMIC)-and lower middle (LMIC)-income countries. We collected information regarding the impact of the pandemic on their self-reported personal finances and sources of income.
FINDINGS: Overall, 32.4% of participants had suffered an adverse financial impact, defined as job loss, inability to meet financial obligations or essential needs, or using savings to meet financial obligations. 8.4% of participants had lost a job (temporarily or permanently); 14.6% of participants were unable to meet financial obligations or essential needs at the time of the survey and 16.3% were using their savings to meet financial obligations. Participants with a post-secondary education were least likely to be adversely impacted (19.6%), compared with 33.4% of those with secondary education and 33.5% of those with pre-secondary education. Similarly, those in the highest wealth tertile were least likely to be financially impacted (26.7%), compared with 32.5% in the middle tertile and 30.4% in the bottom tertile participants. Compared with HICs, financial impact was greater in UMIC [odds ratio of 2.09 (1.88-2.33)] and greatest in LMIC [odds ratio of 16.88 (14.69-19.39)]. HIC participants with the lowest educational attainment suffered less financial impact (15.1% of participants affected) than those with the highest education in UMIC (22.0% of participants affected). Similarly, participants with the lowest education in UMIC experienced less financial impact (28.3%) than those with the highest education in LMIC (45.9%). A similar gradient was seen across country income categories when compared by pre-pandemic wealth status.
INTERPRETATION: The financial impact of the pandemic differs more between HIC, UMIC, and LMIC than between socio-economic categories within a country income level. The most disadvantaged socio-economic subgroups in HIC had a lower financial impact from the pandemic than the most advantaged subgroup in UMIC, with a similar disparity seen between UMIC and LMIC. Continued high levels of infection will exacerbate financial inequity between countries and hinder progress towards the sustainable development goals, emphasising the importance of effective measures to control COVID-19 and, especially, ensuring high vaccine coverage in all countries.
FUNDING: Funding for this study was provided by the Canadian Institutes of Health Research and the International Development Research Centre.
OBJECTIVE: This systematic review aimed to review epidemiological reports to determine the prevalence of MCI and its associated risk factors in LMICs.
METHODS: Medline, Embase, and PsycINFO were searched from inception until November 2019. Eligible articles reported on MCI in population or community-based studies from LMICs and were included as long as MCI was clearly defined.
RESULTS: 5,568 articles were screened, and 78 retained. In total, n = 23 different LMICs were represented; mostly from China (n = 55 studies). Few studies were from countries defined as lower-middle income (n = 14), low income (n = 4), or from population representative samples (n = 4). There was large heterogeneity in how MCI was diagnosed; with Petersen criteria the most commonly applied (n = 26). Prevalence of amnesic MCI (aMCI) (Petersen criteria) ranged from 0.6%to 22.3%. Similar variability existed across studies using the International Working Group Criteria for aMCI (range 4.5%to 18.3%) and all-MCI (range 6.1%to 30.4%). Risk of MCI was associated with demographic (e.g., age), health (e.g., cardio-metabolic disease), and lifestyle (e.g., social isolation, smoking, diet and physical activity) factors.
CONCLUSION: Outside of China, few MCI studies have been conducted in LMIC settings. There is an urgent need for population representative epidemiological studies to determine MCI prevalence in LMICs. MCI diagnostic methodology also needs to be standardized. This will allow for cross-study comparison and future resource planning.
METHODS AND ANALYSIS: Primary outcomes focus on feasibility measures of recruitment, retention, implementation and acceptability of the intervention. Secondary outcomes will include blood pressure, cognitive function, body composition and physical function (including muscle strength and gait speed). Adherence to the dietary intervention will be assessed through collection of biological samples, 24-hour recall and Food Frequency Questionnaire. A subgroup of participants will also complete postintervention focus groups to further explore the feasibility considerations of executing a larger trial, the ability of these individuals to make dietary changes and the barriers and facilitators associated with implementing these changes.
ETHICS AND DISSEMINATION: Ethical approval has been obtained from Monash University Human Research Ethics Committee and Medical Research and Ethics Committee of Malaysia. Results of the study will be disseminated via peer-reviewed publications and presentations at national and international conferences.ISRCTN47562685; Pre-results.
DESIGN: Population-based cross-sectional study.
SETTING: South East Asia Community Observatory HDSS site in Malaysia.
PARTICIPANTS: Of 45 246 participants recruited from 13 431 households, 18 101 eligible adults aged 18-97 years (mean age 47 years, 55.6% female) were included.
MAIN OUTCOME MEASURES: The main outcome was prevalence of multimorbidity. Multimorbidity was defined as the coexistence of two or more chronic conditions per individual. A total of 13 chronic diseases were selected and were further classified into 11 medical conditions to account for multimorbidity. The conditions were heart disease, stroke, diabetes mellitus, hypertension, chronic kidney disease, musculoskeletal disorder, obesity, asthma, vision problem, hearing problem and physical mobility problem. Risk factors for multimorbidity were also analysed.
RESULTS: Of the study cohort, 28.5% people lived with multimorbidity. The individual prevalence of the chronic conditions ranged from 1.0% to 24.7%, with musculoskeletal disorder (24.7%), obesity (20.7%) and hypertension (18.4%) as the most prevalent chronic conditions. The number of chronic conditions increased linearly with age (p<0.001). In the logistic regression model, multimorbidity is associated with female sex (adjusted OR 1.28, 95% CI 1.17 to 1.40, p<0.001), education levels (primary education compared with no education: adjusted OR 0.63, 95% CI 0.53 to 0.74; secondary education: adjusted OR 0.60, 95% CI 0.51 to 0.70; tertiary education: adjusted OR 0.65, 95% CI 0.54 to 0.80; p<0.001) and employment status (working adults compared with retirees: adjusted OR 0.70, 95% CI 0.60 to 0.82, p<0.001), in addition to age (adjusted OR 1.05, 95% CI 1.05 to 1.05, p<0.001).
CONCLUSIONS: The current single-disease services in primary and secondary care should be accompanied by strategies to address complexities associated with multimorbidity, taking into account the factors associated with multimorbidity identified. Future research is needed to identify the most commonly occurring clusters of chronic diseases and their risk factors to develop more efficient and effective multimorbidity prevention and treatment strategies.
METHODS: Data 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.
FINDINGS: 11 143 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.
INTERPRETATION: Not 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.
FUNDING: National Institute for Health Research, Wellcome Trust, WHO, US Alzheimer's Association, and European Research Council.
OBJECTIVE: This systematic review aimed to assess, in middle- and older-aged people, the relationship between dietary sodium intake and cognitive outcomes including cognitive function, risk of cognitive decline, or dementia.
METHODS: Six databases (PubMed, EMBASE, CINAHL, Psych info, Web of Science, and Cochrane Library) were searched from inception to 1 March 2020. Data extraction included information on study design, population characteristics, sodium reduction strategy (trials) or assessment of dietary sodium intake (observational studies), measurement of cognitive function or dementia, and summary of main results. Risk-of-bias assessments were performed using the National Heart, Lung, and Blood Institute (NHLBI) assessment tool.
RESULTS: Fifteen studies met the inclusion criteria including one clinical trial, six cohorts, and eight cross-sectional studies. Studies reported mixed associations between sodium levels and cognition. Results from the only clinical trial showed that a lower sodium intake was associated with improved cognition over six months. In analysis restricted to only high-quality studies, three out of four studies found that higher sodium intake was associated with impaired cognitive function.
CONCLUSION: There is some evidence that high salt intake is associated with poor cognition. However, findings are mixed, likely due to poor methodological quality, and heterogeneous dietary, analytical, and cognitive assessment methods and design of the studies. Reduced sodium intake may be a potential target for intervention. High quality prospective studies and clinical trials are needed.
METHODS: Cytochrome b gene sequences (479 bp) generated from India and available at MalAvi database were used to study the avian haemosporidian prevalence and phylogenetic analysis of lineages at local and world levels.
RESULTS: One common (COLL2) and only once in the study (CYOPOL01, CHD01, CYORUB01, EUMTHA01, GEOCIT01) haemosporidian lineages were discovered. 5.88% prevalence of haemosporidian infection was found in 102 samples belonging to 6 host species. Haemoproteus prevalence was 4.90% across five host species (Phylloscopus trochiloides, Cyornis poliogenys, C. hainanus dialilaemus, C. rubeculoides, Eumiyas thalassinus) and Plasmodium prevalence was 0.98% in Geokichla citrina. Spatial phylogeny at the global level showed that COLL2 lineage, found in C. poliogenys in India, was genetically identical to H. pallidus lineages (COLL2) in parts of Africa, Europe, North America, Malaysia, and the Philippines. The Plasmodium lineage (GEOCIT01) was related to PADOM16 in Egypt, but the sequences were only 93.89% alike.
CONCLUSIONS: Four new lineages of Haemoproteus and one of Plasmodium were reported. COLL2 similarity with other H. pallidus lineages may suggest their hosts as possible infection sources.
METHODS: Women aged 40-74 years, from Segamat, Malaysia, with a mobile phone number, who participated in the South East Asian Community Observatory health survey, (2018) were randomized to an intervention (IG) or comparison group (CG). The IG received a multi-component mHealth intervention, i.e. information about BC was provided through a website, and telephone calls and text messages from community health workers (CHWs) were used to raise BC awareness and navigate women to CBE services. The CG received no intervention other than the usual option to access opportunistic screening. Regression analyses were conducted to investigate between-group differences over time in uptake of screening and variable influences on CBE screening participation.
RESULTS: We recruited 483 women in total; 122/225 from the IG and 144/258 from the CG completed the baseline and follow-up survey. Uptake of CBE by the IG was 45.8% (103/225) whilst 3.5% (5/144) of women from the CG who completed the follow-up survey reported that they attended a CBE during the study period (adjusted OR 37.21, 95% CI 14.13; 98.00, p<0.001). All IG women with a positive CBE attended a follow-up mammogram (11/11). Attendance by IG women was lower among women with a household income ≥RM 4,850 (adjusted OR 0.48, 95% CI 0.20; 0.95, p = 0.038) compared to participants with a household income
METHODS: Individual semi-structured interviews with 22 people (health professionals, cancer survivors, community volunteers and member from a non-governmental organization) and four focus group discussions (n = 22 participants) with women from a local community were conducted. All participants were purposively sampled and female residents registered with the South East Asia Community Observatory aged ≥40 years were eligible to participate in the focus group discussions. Data were transcribed verbatim and analyzed using thematic analysis.
RESULTS: The thematic analysis illuminated barriers, challenges and opportunities across six domains: (i) personal experiences and barriers to help-seeking as well as financial and travel access barriers; (ii) primary care challenges (related to delivering clinical breast examination and teaching breast-self-examination); (iii) secondary care challenges (related to mammogram services); (iv) disconnection between secondary and primary care breast cancer screening pathways; and (v) opportunities to improve breast cancer early detection relating to community civil service society activities (i.e. awareness raising, support groups, addressing stigma/embarrassment and encouraging husbands to support women) and vi) links between public healthcare personnel and community (i.e. improving breast self-examination education, clinical breast examination provision and subsidised mammograms).
CONCLUSION: The results point to a variety of reasons for low uptake and, therefore, to the complex nature of improving breast cancer screening and early detection. There is a need to adopt a systems approach to address this complexity and to take account of the socio-cultural context of communities in order, in turn, to strengthen cancer control policy and practices in Malaysia.
OBJECTIVES: This study aimed to collect real-world cost and HRQOL data, and investigate their associations with multiple disease-severity indicators among AD patients in Thailand.
METHODS: We recruited AD patients aged ≥60 years accompanied by their caregivers at a university-affiliated tertiary hospital. A one-time structured interview was conducted to collect disease-severity indicators, HRQOL, and caregiving information using standardized tools. The hospital's database was used to retrieve healthcare resource utilization occurred over 6 months preceding the interview date. Costs were annualized and stratified based on cognitive status. Generalized linear models were employed to evaluate determinants of costs and HRQOL.
RESULTS: Among 148 community-dwelling patients, average annual total societal costs of AD care were $8014 (95% confidence interval [CI]: $7295-$8844) per patient. Total costs of patients with severe stage ($9860; 95% CI: $8785-$11 328) were almost twice as high as those of mild stage ($5524; 95% CI: $4649-$6593). The major cost driver was direct medical costs, particularly those incurred by AD prescriptions. Functional status was the strongest determinant for both total costs and patient's HRQOL (P value