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Background Peru faces challenges to provide adequate care to stroke patients. Length of hospitalization and in-hospital mortality are two well-known indicators of stroke care. We aimed to describe the length of stay (LOS) of stroke in Peru, and to assess in-hospital mortality risk due to stroke, and subtypes. Methods This retrospective cohort study used hospitalization registries coding with ICD-10 from 2002 to 2017 (N = 98,605) provided by the Ministry of Health; in-hospital mortality was available for 2016–2017 (N = 6,566). Stroke cases aged ≥35 years were divided into subarachnoid hemorrhage (I60), intracerebral hemorrhage (I61), cerebral infarction (I63), and stroke not specified as hemorrhage or infarction (I64). Data included stroke LOS and in-hospital mortality; socio-demographic and clinical variables. We fitted a region- and hospital level-stratified Weibull proportional hazard model to assess the in-hospital mortality. Results The median LOS was 7 days (IQR: 4–13). Hemorrhagic strokes had median LOS longer than ischemic strokes and stroke not specified as hemorrhage or infarction (P =

Background There are several ecological studies, but few studies of the prevalence of SARS-COV-2 at high altitude. We aimed to estimate the population-based seroprevalence of SARS-COV-2 in three settings of Cusco at the end of the first wave among adults. Methods A population-based survey was conducted in September 2020, in three settings in the region of Cusco: (1) Cusco city at 3,300 meters above the sea level (m.a.s.l.), (2) the periphery of Cusco (Santiago, San Jerónimo, San Sebastián, and Wanchaq) at 3,300 m.a.s.l., and (3) Quillabamba city, located at 1,050 m.a.s.l. People aged ≥ 18 years within a family unit were included. The diagnosis of SARS-CoV-2 infection was based on identifying anti- SARS-CoV-2 total antibodies (IgM and IgG) in serum using the Elecsys Anti-SARS-CoV-2 chemiluminescence test. Results We enrolled 1924 participants from 712 families. Of the total, 637 participants were anti-SARS-CoV-2 seropositive. Seroprevalence was 38.8% (95% CI [33.4%–44.9%]) in Cusco city, 34.9% (95% CI [30.4%–40.1%]) in the periphery of Cusco, and 20.3% (95% CI [16.2%–25.6%]) in Quillabamba. In 141 families (19.8%; 95% CI [17.0%–22.8%]) the whole members were positive to the test. Living with more than three persons in the same house, a positive COVID-19 case at home, and a member who died in the last five months were factors associated with SARS-COV-2 seropositivity. Dysgeusia/dysosmia was the symptom most associated with seropositivity (aPR = 2.74, 95% CI [2.41–3.12]); whereas always wearing a face shield (aPR = 0. 73; 95% CI [0.60–0.89]) or a facial mask (aPR = 0.76, 95% CI [0.63–0. 92) reduced that probability. Conclusions A great proportion of Cusco’s city inhabitants presented anti-SARS-CoV-2 antibodies at the end of the first wave, with significant differences between settings. Wearing masks and face shields were associated with lower rate of seropositivity; however, efforts must be made to sustain them over time since there is still a high proportion of susceptible people.

Background Understanding the relationship between BMI and blood pressure requires assessing whether this association is similar or differs across population groups. This study aimed to assess the association between body mass index (BMI) and blood pressure levels, and how these associations vary between socioeconomic groups and geographical settings. Methods Data from the National Demographic Health Survey of Peru from 2014 to 2019 was analyzed considering the complex survey design. The outcomes were levels of systolic (SBP) and diastolic blood pressure (DBP), and the exposure was BMI. Exposure and outcomes were fitted as continuous variables in a non-linear quadratic regression model. We explored effect modification by six socioeconomic and geographical variables (sex, age, education level, socioeconomic position, study area, and altitude), fitting an interaction term between each of these variables and BMI. Results Data from 159, 940 subjects, mean age 44.4 (SD: 17.1), 54.6% females, was analyzed. A third (34.0%) of individuals had ≥12 years of education, 24.7% were from rural areas, and 23.7% lived in areas located over 2,500 m above sea level. In the overall sample mean BMI was 27.1 (SD: 4.6) kg/m2, and mean SBP and DBP were 122.5 (SD: 17.2) and 72.3 (SD: 9.8) mmHg, respectively. In the multivariable models, greater BMI levels were associated with higher SBP (p-value < 0.001) and DBP (p-value < 0.001). There was strong evidence that sex, age, education level, and altitude were effect modifiers of the association between BMI and both SBP and DBP. In addition to these socio-demographic variables, socioeconomic position and study area were also effect modifiers of the association between BMI and DBP, but not SBP. Conclusions The association between BMI and levels of blood pressure is not uniform on a range of socio-demographic and geographical population groups. This characterization can inform the understanding of the epidemiology and rise of blood pressure in a diversity of low-resource settings.

Objective To synthetize the scientific evidence on the association between serum lipids and premature mortality in Latin America (LA). Methods Five data bases were searched from inception without language restrictions: Embase, Medline, Global Health, Scopus and LILACS. Population-based studies following random sampling methods were identified. The exposure variable was lipid biomarkers (e.g., total, LDL- or HDL- cholesterol). The outcome was all-cause and cause-specific mortality. The risk of bias was assessed following the Newcastle-Ottawa criteria. Results were summarized qualitatively. Results The initial search resulted in 264 abstracts, five (N = 27,903) were included for the synthesis. Three papers reported on the same study from Puerto Rico (baseline in 1965), one was from Brazil (1996) and one from Peru (2007). All reports analysed different exposure variables and used different risk estimates (relative risks, hazard ratios or odds ratios). None of the reviewed reports showed strong association between individual lipid biomarkers and all-cause or cardiovascular mortality. Conclusion The available evidence is outdated, inconsistently reported on several lipid biomarker definitions and used different methods to study the long-term mortality risk. These findings strongly support the need to better ascertain the mortality risk associated with lipid biomarkers in LA.

Background The underlying cause of death is used to study country and global mortality trends and profiles. The final cause of death could also inform the ultimately cause of death in individuals with underlying conditions. Whether there is a pattern between the underlying and final cause of death has not been explored using national death registries. We studied what final causes of death were most common among selected underlying causes using national death registries in Peru, 2015. Methods Underlying and final causes of death were classified according to their ICD-10 codes. Underlying causes included chronic kidney disease (CKD), chronic obstructive pulmonary disease (COPD), hypertension (HTN), diabetes, and selected cancers (cervix, breast, stomach, prostate, and lung). Final causes were categorized as: communicable, cardiovascular, and cancers. Descriptive statistics were used. Results A total of 77,065 death registries were analyzed; cases had a mean age of 69.4 (SD: 19.3) years at death and were mostly men (53.9%). When the underlying cause was HTN, the most frequent final cause was cardiovascular diseases (82.3%). For all the other underlying causes, the most frequent final cause was communicable diseases: COPD (86.4%), CKD (79.3%), cancer (76.5%), and diabetes (68.3%). Conclusions In four selected underlying causes of death there was a divergence with respect to the final cause, suggesting there was a shift from non-communicable to communicable causes. Although efforts should be deployed to prevent underlying non-communicable diseases, potential communicable complications should not be neglected.

Objectives. We aimed to assess if Caesarean section is a risk factor for overnutrition in early- and late-childhood, and to assess the magnitude of the effect of child- versus family-related variables in these risk estimates.Methods. Longitudinal data from Peruvian children from the Young Lives Study was used. Outcomes assessed were overweight, obesity, overnutrition (overweight plus obesity), and central obesity (waist circumference) at the age 5 (first follow-up) and 7 (second follow-up) years. The exposure of interests was delivery by Caesarean section. Relative risks (RR) and 95% confidence intervals (95% CI) were calculated using multivariable models adjusted for child-related (e.g., birth weight) and family-related (e.g., maternal nutritional status) variables.Results. At baseline, mean age was 11.7 (± 3.5) months and 50.1% were boys. Children born by Caesarean section were 15.6%. The 10.5% of the children were overweight and 2.4% were obese. For the obesity outcome, data from 6,038 and 9,625 children-years was included from baseline to the first and second follow-up, respectively. Compared to those who did not experience Caesarean delivery, the risk of having obesity was higher in the group born by Caesarean: RRs were higher at early-childhood (first follow-up: 2.25; 95% CI [1.36–3.74]) than later in life (second follow-up: 1.57; 95% CI [1.02–2.41]). Family-related variables had a greater effect in attenuating the risk estimates for obesity at the first, than at the second follow-up.Conclusion. Our results suggest a higher probability of developing obesity, but not overweight, among children born by Caesarean section delivery. The magnitude of risk estimates decreased over time, and family-related variables had a stronger effect on the risk estimates at early-childhood.

Background. Sleep duration, either short or long, has been associated with diseases such as obesity, type-2 diabetes and cardiovascular diseases. Characterizing the prevalence and patterns of sleep duration at the population-level, especially in resource-constrained settings, will provide informative evidence on a potentially modifiable risk factor. The aim of this study was to explore the patterns of sleep duration in the Peruvian adult and adolescent population, together with its socio-demographic profile.Material and Methods. A total of 12,424 subjects, mean age 35.8 years (SD ±17.7), 50.6% males, were included in the analysis. This is a cross-sectional study, secondary analysis of the Use of Time National Survey conducted in 2010. We used weighted means and proportions to describe sleep duration according to socio-demographic variables (area and region; sex; age; education attainment; asset index; martial and job status). We used Poisson regressions, taking into account the multistage sampling design of the survey, to calculate crude and adjusted prevalence ratios (PR) and 95% confidence intervals (95% CI). Main outcomes were short- (