The Sustainable Development Goal (SDG) target 3.4 is to reduce premature mortality from non-communicable diseases (NCDs) by a third by 2030 relative to 2015 levels, and to promote mental health and ...wellbeing. We used data on cause-specific mortality to characterise the risk and trends in NCD mortality in each country and evaluate combinations of reductions in NCD causes of death that can achieve SDG target 3.4. Among NCDs, ischaemic heart disease is responsible for the highest risk of premature death in more than half of all countries for women, and more than three-quarters for men. However, stroke, other cardiovascular diseases, and some cancers are associated with a similar risk, and in many countries, a higher risk of premature death than ischaemic heart disease. Although premature mortality from NCDs is declining in most countries, for most the pace of change is too slow to achieve SDG target 3.4. To investigate the options available to each country for achieving SDG target 3.4, we considered different scenarios, each representing a combination of fast (annual rate achieved by the tenth best performing percentile of all countries) and average (median of all countries) declines in risk of premature death from NCDs. Pathways analysis shows that every country has options for achieving SDG target 3.4. No country could achieve the target by addressing a single disease. In at least half the countries, achieving the target requires improvements in the rate of decline in at least five causes for women and in at least seven causes for men to the same rate achieved by the tenth best performing percentile of all countries. Tobacco and alcohol control and effective health-system interventions—including hypertension and diabetes treatment; primary and secondary cardiovascular disease prevention in high-risk individuals; low-dose inhaled corticosteroids and bronchodilators for asthma and chronic obstructive pulmonary disease; treatment of acute cardiovascular diseases, diabetes complications, and exacerbations of asthma and chronic obstructive pulmonary disease; and effective cancer screening and treatment—will reduce NCD causes of death necessary to achieve SDG target 3.4 in most countries.
Simplified blood pressure (BP) screening approaches have been proposed. However, evidence is limited to a few countries and has not documented the cardiovascular risk amongst missed hypertension ...cases, limiting the uptake of these simplified approaches. We quantified the proportion of missed, over-diagnosed, and consistently identified hypertension cases and the 10-year cardiovascular risk in these groups.
We used 60 WHO STEPS surveys (cross-sectional and nationally representative; n = 145,174) conducted in 60 countries in 6 world regions between 2004 and 2019. Nine simplified approaches were compared against the standard (average of the last 2 of 3 BP measurements). The 10-year cardiovascular risk was computed with the 2019 World Health Organization Cardiovascular Risk Charts. We used t tests to compare the cardiovascular risk between the missed and over-diagnosed cases and the consistent hypertension cases. We used Poisson multilevel regressions to identify risk factors for missed cases (adjusted for age, sex, body mass index, and 10-year cardiovascular risk). Across all countries, compared to the standard approach, the simplified approach that missed the fewest cases was using the second BP reading if the first BP reading was 130-145/80-95 mm Hg (5.62%); using only the second BP reading missed 5.82%. The simplified approach with the smallest over-diagnosis proportion was using the second BP reading if the first BP measurement was ≥140/90 mm Hg (3.03%). In many countries, cardiovascular risk was not significantly different between the missed and consistent hypertension groups, yet the mean was slightly lower amongst missed cases. Cardiovascular risk was positively associated with missed hypertension depending on the simplified approach. The main limitation of the work is the cross-sectional design.
Simplified BP screening approaches seem to have low misdiagnosis rates, and cardiovascular risk could be lower amongst missed cases than amongst consistent hypertension cases. Simplified BP screening approaches could be included in large screening programmes and busy clinics.
Background
Screening for type 2 diabetes mellitus (T2DM) targets people aged 35+ years and those with overweight/obesity. With mounting evidence on young‐onset T2DM and T2DM patients with lean ...phenotypes, it is worth revising the screening criteria to include younger and leaner adults. We quantified the mean age and body mass index (BMI; kg/m2) at T2DM diagnosis in 56 countries.
Methods
Descriptive cross‐sectional analysis of WHO STEPS surveys. We analysed adults (25–69 years) with new T2DM diagnosis (not necessarily T2DM onset) as per fasting plasma glucose ≥126 mg/dL measured during the survey. For people with new T2DM diagnosis, we summarized the mean age and the proportion of each five‐year age group; also, we summarized the mean BMI and the proportion of mutually exclusive BMI categories.
Results
There were 8695 new T2DM patients. Overall, the mean age at T2DM diagnosis was 45.1 years in men and 45.0 years in women; and the mean BMI at T2DM diagnosis was 25.2 in men and 26.9 in women. Overall, in men, 10.3% were 25–29 years and 8.5% were 30–34 years old; in women, 8.6% and 12.5% were 25–29 years and 30–34 years old, respectively. 48.5% of men and 37.3% of women were in the normal BMI category.
Conclusions
A non‐negligible proportion of new T2DM patients were younger than 35 years. Many new T2DM patients were in the normal weight range. Guidelines for T2DM screening may consider revising the age and BMI criteria to incorporate young and lean adults.
Aims
The use of continuous glucose monitors (CGMs) has been shown to have positive impact on diabetes management for people with type 1 diabetes (T1DM), type 2 diabetes (T2DM) and gestational ...diabetes (GDM) in high‐income countries. However, as useful as CGMs are, the experience in low‐ and middle‐income countries (LMICs) is limited and has not been summarized.
Methods
A scoping review of the scientific literature was conducted. Medline, Embase, Global Health and Scopus were used to seek original research conducted in LMICs. The search results were screened by two reviewers independently. We included studies assessing health outcomes following the use of CGMs at the individual level (e.g. glycaemic control or complications) and at the health system level (e.g. barriers, facilitators and cost‐effectiveness) in English, Portuguese, Spanish and French. Results were summarized narratively.
Results
From 4772 records found in database search, 27 reports were included; most of them from China (n = 7), Colombia (n = 5) and India (n = 4). Thirteen reports studied T1DM, five T2DM, seven both T1DM and T2DM and two GDM. Seven reports presented results of experimental studies (five randomized trials and two quasi‐experimental); two on cost‐effective analysis and the remaining 18 were observational. Studies showed that CGMs improved surrogate glycaemic outcomes (HbA1c reduction), hard endpoints (lower hospitalization rates and diabetes complications) and patient‐oriented outcomes (quality of life). However, several caveats were identified: mostly observational studies, few participants in trials, short follow‐up and focused on surrogate outcomes.
Conclusions
The scoping review identified that studies about CGMs in LMICs have several limitations. Stronger study designs, appropriate sample sizes and the inclusion of patient‐important outcomes should be considered to inform the evidence about CGMs for the management of people with diabetes in LMICs.
Summary
Type 2 diabetes mellitus (T2DM) is associated with a high mortality risk, although the magnitude of this association remains unknown in Latin America (LA). We aimed to assess the strength of ...the association between T2DM and all‐cause and cause‐specific mortality in population‐based cohort studies in LA.
Systematic review and meta‐analysis: inclusion criteria were (1) men and women 18 years old and above with T2DM; (2) study outcomes all‐cause and/or cause‐specific mortality; and (3) using people without T2DM as comparison group. Five databases (Scopus, Medline, Embase, Global Health, and LILACS) were searched. Risk of bias was evaluated with the ROBINS‐I criteria. Initially, there were 979 identified studies, of which 17 were selected for qualitative synthesis; 14 were included in the meta‐analysis (N = 416 821). Self‐reported T2DM showed a pooled relative risk (RR) of 2.49 for all‐causes mortality (I‐squared I2 = 85.7%, p < 0.001; 95% confidence interval CI, 1.96‐3.15). T2DM based on a composite definition was associated with a 2.26‐fold higher all‐cause mortality (I2 = 93.9%, p < 0.001; 95% CI, 1.36‐3.74). The pooled risk estimates were similar between men and women, although higher at younger ages. The pooled RR for cardiovascular mortality was 2.76 (I2 = 59.2%; p < 0.061; 95% CI, 1.99‐3.82) and for renal mortality 15.85 (I2 = 0.00%; p < 0.645; 95% CI, 9.82‐25.57). Using available population‐based cohort studies, this work has identified and estimated the strength of the association between T2DM and mortality in LA. The higher mortality risk compared with high‐income countries deserves close attention from health policies makers and clinicians to improve diabetes care and control hence preventing complications and delaying death.
This systematic review had three aims: i) to determine the frequency of anosmia (or other smell disorders) and dysgeusia (or other taste disorders) in COVID-19 patients; ii) to determine whether ...anosmia or dysgeusia are independently associated with COVID-19 diagnosis; and iii) to determine whether anosmia or dysgeusia are prognostic factors for impaired outcomes among COVID-19 patients.
On April 20
, 2020, we search MEDLINE, Embase, Global Health, Scopus, Web of Science and MedXriv. We used terms related to COVID-19, smell and taste disorders. We selected case series, cross-sectional, case-control and cohort studies. We included studies with COVID-19 patients describing their symptoms; studies that compared smell and taste disorders between COVID-19 patients and otherwise healthy subjects; and studies comparing smell and taste disorders between COVID-19 severe and mild/moderate cases. Because of methodological heterogeneity and the limited number of results, a qualitative synthesis is presented.
From 31 reports, we selected six (n=2,757). Six studies reported the proportion of smell and taste disorders among COVID-19 patients. Two reports studied whether smell and taste disorders were independently associated with COVID-19 diagnosis. No reports studied the association with impaired outcomes among COVID-19 patients. The frequency of anosmia ranged between 22%-68%. The definition of taste disorders varied greatly, with dysgeusia present in 33% and ageusia in 20%. People who reported loss of smell and taste had six-fold higher odds of being COVID-19 positive; similarly, anosmia and ageusia were associated with 10-fold higher odds of COVID-19 diagnosis.
The frequency of smell and taste disorders is as high as other symptoms, thus, at least anosmia for which the definition was more consistent, could be included in lists of COVID-19 symptoms. Although there is promising evidence, it is premature to conclude that smell and taste disorders are strongly associated with COVID-19 diagnosis.
PROSPERO CRD42020181308.
The burden of obesity differs by socioeconomic status. We aimed to characterise the prevalence of obesity among adult men and women in Latin America and the Caribbean by socioeconomic measures and ...the shifting obesity burden over time.
We did a cross-sectional series analysis of obesity prevalence by socioeconomic status by use of national health surveys done between 1998 and 2017 in 13 countries in Latin America and the Caribbean. We generated equiplots to display inequalities in, the primary outcome, obesity by wealth, education, and residence area. We measured obesity gaps as the difference in percentage points between the highest and lowest obesity prevalence within each socioeconomic measure, and described trends as well as changing patterns of the obesity burden over time.
479 809 adult men and women were included in the analysis. Obesity prevalence across countries has increased over time, with distinct patterns emerging by wealth and education indices. In the most recent available surveys, obesity was most prevalent among women in Mexico in 2016, and the least prevalent among women in Haiti in 2016. The largest gap between the highest and lowest obesity estimates by wealth was observed in Honduras among women (21·6 percentage point gap), and in Peru among men (22·4 percentage point gap), compared with a 3·7 percentage point gap among women in Brazil and 3·3 percentage points among men in Argentina. Urban residents consistently had a larger burden than their rural counterparts in most countries, with obesity gaps ranging from 0·1 percentage points among women in Paraguay to 15·8 percentage points among men in Peru. The trend analysis done in five countries suggests a shifting of the obesity burden across socioeconomic groups and different patterns by gender. Obesity gaps by education in Mexico have reduced over time among women, but increased among men, whereas the gap has increased among women but remains relatively constant among men in Argentina.
The increase in obesity prevalence in the Latin American and Caribbean region has been paralleled with an unequal distribution and a shifting burden across socioeconomic groups. Anticipation of the establishment of obesity among low socioeconomic groups could provide opportunities for societal gains in primordial prevention.
None.
Research has shown that X-rays and fundus images can classify gender, age group, and race, raising concerns about bias and fairness in medical AI applications. However, the potential for ...physiological sounds to classify sociodemographic traits has not been investigated. Exploring this gap is crucial for understanding the implications and ensuring fairness in the field of medical sound analysis. We aimed to develop classifiers to determine gender (men/women) based on heart sound recordings and using machine learning (ML). Data-driven ML analysis. We utilized the open-access CirCor DigiScope Phonocardiogram Dataset obtained from cardiac screening programs in Brazil. Volunteers < 21 years of age. Each participant completed a questionnaire and underwent a clinical examination, including electronic auscultation at four cardiac points: aortic (AV), mitral (MV), pulmonary (PV), and tricuspid (TV). We used Mel-frequency cepstral coefficients (MFCCs) to develop the ML classifiers. From each patient and from each auscultation sound recording, we extracted 10 MFCCs. In sensitivity analysis, we additionally extracted 20, 30, 40, and 50 MFCCs. The most effective gender classifier was developed using PV recordings (AUC ROC = 70.3%). The second best came from MV recordings (AUC ROC = 58.8%). AV and TV recordings produced classifiers with an AUC ROC of 56.4% and 56.1%, respectively. Using more MFCCs did not substantially improve the classifiers. It is possible to classify between males and females using phonocardiogram data. As health-related audio recordings become more prominent in ML applications, research is required to explore if these recordings contain signals that could distinguish sociodemographic features.Research has shown that X-rays and fundus images can classify gender, age group, and race, raising concerns about bias and fairness in medical AI applications. However, the potential for physiological sounds to classify sociodemographic traits has not been investigated. Exploring this gap is crucial for understanding the implications and ensuring fairness in the field of medical sound analysis. We aimed to develop classifiers to determine gender (men/women) based on heart sound recordings and using machine learning (ML). Data-driven ML analysis. We utilized the open-access CirCor DigiScope Phonocardiogram Dataset obtained from cardiac screening programs in Brazil. Volunteers < 21 years of age. Each participant completed a questionnaire and underwent a clinical examination, including electronic auscultation at four cardiac points: aortic (AV), mitral (MV), pulmonary (PV), and tricuspid (TV). We used Mel-frequency cepstral coefficients (MFCCs) to develop the ML classifiers. From each patient and from each auscultation sound recording, we extracted 10 MFCCs. In sensitivity analysis, we additionally extracted 20, 30, 40, and 50 MFCCs. The most effective gender classifier was developed using PV recordings (AUC ROC = 70.3%). The second best came from MV recordings (AUC ROC = 58.8%). AV and TV recordings produced classifiers with an AUC ROC of 56.4% and 56.1%, respectively. Using more MFCCs did not substantially improve the classifiers. It is possible to classify between males and females using phonocardiogram data. As health-related audio recordings become more prominent in ML applications, research is required to explore if these recordings contain signals that could distinguish sociodemographic features.
Leptospirosis is a worldwide prevalent zoonosis and chronic kidney disease (CKD) is a leading global disease burden. Because of pathophysiological changes in the kidney, it has been suggested that ...these conditions may be associated. However, the extent of this interaction has not been synthetized. We aimed to systematically review and critically appraise the evidence on the association between leptospirosis and CKD.
Observational studies with a control group were selected. Leptospirosis, confirmed with laboratory methods, and CKD also based on a laboratory assessment, were the exposures and outcomes of interest. The search was conducted in EMBASE, MEDLINE, Global Health, Scopus and Web of Science. Studies selected for qualitative synthesis were assessed for risk of bias following the Newcastle-Ottawa Scale. 5,981 reports were screened, and 2 (n = 3,534) were included for qualitative synthesis. The studies were conducted in Taiwan and Nicaragua; these reported cross-sectional and longitudinal estimates. In the general population, the mean estimated glomerular filtration rate (eGFR) was lower (p<0.001) in people testing positive for antileptospira antibodies (eGFR = 98.3) than in negative controls (eGFR = 100.8). Among sugarcane applicants with high creatinine, those who were seropositive had lower eGFR (mean difference: -10.08). In a prospective analysis, people with high antileptospira antibodies titer at baseline and follow-up, had worse eGFR (p<0.05).
Although the available evidence suggests there may be a positive association between leptospirosis and CKD, whereby leptospirosis could be a risk factor for CKD, it is still premature to draw conclusions. There is an urgent need for research on this association.
The COVID-19 pandemic has attracted the attention of researchers and clinicians whom have provided evidence about risk factors and clinical outcomes. Research on the COVID-19 pandemic benefiting from ...open-access data and machine learning algorithms is still scarce yet can produce relevant and pragmatic information. With country-level pre-COVID-19-pandemic variables, we aimed to cluster countries in groups with shared profiles of the COVID-19 pandemic.
Unsupervised machine learning algorithms (k-means) were used to define data-driven clusters of countries; the algorithm was informed by disease prevalence estimates, metrics of air pollution, socio-economic status and health system coverage. Using the one-way ANOVA test, we compared the clusters in terms of number of confirmed COVID-19 cases, number of deaths, case fatality rate and order in which the country reported the first case.
The model to define the clusters was developed with 155 countries. The model with three principal component analysis parameters and five or six clusters showed the best ability to group countries in relevant sets. There was strong evidence that the model with five or six clusters could stratify countries according to the number of confirmed COVID-19 cases (p<0.001). However, the model could not stratify countries in terms of number of deaths or case fatality rate.
: A simple data-driven approach using available global information before the COVID-19 pandemic, seemed able to classify countries in terms of the number of confirmed COVID-19 cases. The model was not able to stratify countries based on COVID-19 mortality data.
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