Contribution of modifiable risk factors for hypertension and type-2 diabetes in Peruvian resource-limited settings.

BACKGROUND: It is important to understand the local burden of non-communicable diseases including within-country heterogeneity. The aim of this study was to characterise hypertension and type-2 diabetes profiles across different Peruvian geographical settings emphasising the assessment of modifiable risk factors. METHODS: Analysis of the CRONICAS Cohort Study baseline assessment was conducted. Cardiometabolic outcomes were blood pressure categories (hypertension, prehypertension, normal) and glucose metabolism disorder status (diabetes, prediabetes, normal). Exposures were study setting and six modifiable factors (smoking, alcohol drinking, leisure time and transport-related physical activity levels, TV watching, fruit/vegetables intake and obesity). Poisson regression models were used to report prevalence ratios (PR). Population attributable risks (PAR) were also estimated. RESULTS: Data from 3238 participants, 48.3% male, mean age 45.3 years, were analysed. Age-standardised (WHO population) prevalence of prehypertension and hypertension was 24% and 16%, whereas for prediabetes and type-2 diabetes it was 18% and 6%, respectively. Outcomes varied according to study setting (p<0.001). In multivariable model, hypertension was higher among daily smokers (PR 1.76), heavy alcohol drinkers (PR 1.61) and the obese (PR 2.06); whereas only obesity (PR 2.26) increased the prevalence of diabetes. PAR showed that obesity was an important determinant for hypertension (15.7%) and type-2 diabetes (23.9%). CONCLUSIONS: There is an evident heterogeneity in the prevalence of and risk factors for hypertension and diabetes within Peru. Prehypertension and prediabetes are highly prevalent across settings. Our results emphasise the need of understanding the epidemiology of cardiometabolic conditions to appropriately implement interventions to tackle the burden of non-communicable diseases

Impact of urbanisation and altitude on the incidence of, and risk factors for, hypertension.

BACKGROUND: Most of the data regarding the burden of hypertension in low-income and middle-income countries comes from cross-sectional surveys instead of longitudinal studies. We estimated the incidence of, and risk factors for, hypertension in four study sites with different degree of urbanisation and altitude. METHODS: Data from the CRONICAS Cohort Study, conducted in urban, semiurban and rural areas in Peru, was used. An age-stratified and sex-stratified random sample of participants was taken from the most updated census available in each site. Hypertension was defined as systolic blood pressure ≥140 mm Hg, or diastolic blood pressure ≥90 mm Hg, or self-report physician diagnosis and current treatment. The exposures were study site and altitude as well as modifiable risk factors. Incidence, incidence rate ratios (IRRs), 95% CIs and population-attributable fractions (PAFs) were estimated using generalised linear models. RESULTS: Information from 3237 participants, mean age 55.8 (SD±12.7) years, 48.4% males, was analysed. Overall baseline prevalence of hypertension was 19.7% (95% CI 18.4% to 21.1%). A total of 375 new cases of hypertension were recorded, including 5266 person-years of follow-up, with an incidence of 7.12 (95% CI 6.44 to 7.88) per 100 person-years. Individuals from semiurban site were at higher risk of hypertension compared with highly urbanised areas (IRR=1.76; 95% CI 1.39 to 2.23); however, those from high-altitude sites had a reduced risk (IRR=0.74; 95% CI 0.58 to 0.95). Obesity was the leading risk factor for hypertension with a great variation according to study site with PAF ranging from 12.5% to 42.4%. CONCLUSIONS: Our results suggest heterogeneity in the progression towards hypertension depending on urbanisation and site altitude

Sodium and Potassium Consumption in a Semi-Urban Area in Peru: Evaluation of a Population-Based 24-Hour Urine Collection.

Despite the negative effects of high sodium and low potassium consumption on cardiovascular health, their consumption has not been quantified in sites undergoing urbanization. We aimed to determine the sodium and potassium consumption in a semi-urban area in Peru with a cross-sectional study. 24-h urine samples were collected. The outcomes were mean consumption of sodium and potassium, as well as adherence to their consumption recommendation: <2 g/day and ≥3.51 g/day, respectively. Bivariate analyses were conducted to identify socio-economic and clinical variables associated with the consumption recommendations of 602 participants, complete urine samples were found in 409: mean age of participants was 45.7 (standard deviation (SD): 16.2) years and 56% were women. The mean sodium and potassium consumption was 4.4 (SD: 2.1) and 2.0 (SD: 1.2) g/day. The sodium and potassium recommendation was met by 7.1% and 13.7% of the study sample; none of the participants met both recommendations. People not adherent to the sodium recommendation had higher diastolic (73.1 mmHg vs. 68.2 mmHg, p = 0.015) and systolic (113.1 mmHg vs. 106.3 mmHg, p = 0.047) blood pressure than those who comply with the recommendation. Public health actions ought to be implemented in areas undergoing urbanization to improve sodium and potassium consumption at the population level

Does physicians’ right to strike outweigh students’ right to an education? The on-going ethical dilemma in Peru

Although often viewed as an action of last resort, going on strike remains a legal and often effective option for physicians seeking labor improvements and better working conditions. Indeed, in some countries, there have been reports of strikes by physicians 1 2, followed by ensuing discussions of potential ethical implications 3–5. However, little has been said about the consequences of such a mass labor stoppage on undergraduate medical education – and those students who aspire to the profession. In Peru, physicians from the Peruvian National Social Insurance (EsSalud) went on a 33-day strike (August 7 to September 8), effectively limiting medical services to only emergency and critical care units. Furthermore, per EsSalud's labor guidelines (prepared for purposes of the strike), all academic activity within affiliated teaching hospitals was explicitly forbidden during the strike

Impact of Food Assistance Programs on Obesity in Mothers and Children: A Prospective Cohort Study in Peru.

Objectives. To assess obesity risk among mothers participating in Community Kitchens and children participating in Glass of Milk (Peru food assistance programs). Methods. We analyzed prospective data from the Young Lives study. The exposure consisted in varying degrees of benefit from any of the programs (no participation in any of the programs, program participation for some months, or program participation nearly every month) at baseline (2006–2007). The outcome was overweight and obesity in mothers and children at follow-up (2009–2010). Results. Prevalence of childhood overweight and obesity was 15.5% and 5.1%, respectively; the corresponding figures for mothers were 40.5% and 14.6%. Children exposed nearly every month to the Glass of Milk program had a 65% lower risk of becoming obese compared with children not participating in the program (relative risk [RR] = 0.35; 95% confidence interval [CI] = 0.18, 0.66). Mothers participating frequently in the Community Kitchens program had almost twice the risk of becoming obese compared with those who did not participate (RR = 1.93; 95% CI = 1.18, 3.15). Conclusions. Participating in food assistance programs in Peru was associated with a lower risk of obesity in children and greater risk of obesity in mothers.Revisión por pare

Large Language Models for Integrating Social Determinant of Health Data: A Case Study on Heart Failure 30-Day Readmission Prediction

Social determinants of health (SDOH) $-$ the myriad of circumstances in which people live, grow, and age $-$ play an important role in health outcomes. However, existing outcome prediction models often only use proxies of SDOH as features. Recent open data initiatives present an opportunity to construct a more comprehensive view of SDOH, but manually integrating the most relevant data for individual patients becomes increasingly challenging as the volume and diversity of public SDOH data grows. Large language models (LLMs) have shown promise at automatically annotating structured data. Here, we conduct an end-to-end case study evaluating the feasibility of using LLMs to integrate SDOH data, and the utility of these SDOH features for clinical prediction. We first manually label 700+ variables from two publicly-accessible SDOH data sources to one of five semantic SDOH categories. Then, we benchmark performance of 9 open-source LLMs on this classification task. Finally, we train ML models to predict 30-day hospital readmission among 39k heart failure (HF) patients, and we compare the prediction performance of the categorized SDOH variables with standard clinical variables. Additionally, we investigate the impact of few-shot LLM prompting on LLM annotation performance, and perform a metadata ablation study on prompts to evaluate which information helps LLMs accurately annotate these variables. We find that some open-source LLMs can effectively, accurately annotate SDOH variables with zero-shot prompting without the need for fine-tuning. Crucially, when combined with standard clinical features, the LLM-annotated Neighborhood and Built Environment subset of the SDOH variables shows the best performance predicting 30-day readmission of HF patients.Comment: 36 pages including references and appendix. This is a work in progres

Association between body mass index and blood pressure levels across socio-demographic groups and geographical settings: analysis of pooled data in Peru.

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

Data pooling efforts in Africa and Latin America.

Correspondenc

The contribution of specific non-communicable diseases to the achievement of the Sustainable Development Goal 3.4 in Peru

Background Non-communicable diseases (NCDs) have received political attention and commitment, yet surveillance is needed to measure progress and set priorities. Building on global estimates suggesting that Peru is not on target to meet the Sustainable Development Goal 3.4, we estimated the contribution of various NCDs to the change in unconditional probability of dying from NCDs in 25 regions in Peru. Methods Using national death registries and census data, we estimated the unconditional probability of dying between ages 30 and 69 from any and from each of the following NCDs: cardiovascular, cancer, diabetes, chronic respiratory diseases and chronic kidney disease. We estimated the contribution of each NCD to the change in the unconditional probability of dying from any of these NCDs between 2006 and 2016. Results The overall unconditional probability of dying improved for men (21.4%) and women (23.3%). Cancer accounted for 10.9% in men and 13.7% in women of the overall reduction; cardiovascular diseases also contributed substantially: 11.3% in men) and 9.8% in women. Consistently in men and women and across regions, diabetes moved in the opposite direction of the overall reduction in the unconditional probability of dying from any selected NCD. Diabetes contributed a rise in the unconditional probability of 3.6% in men and 2.1% in women. Conclusions Although the unconditional probability of dying from any selected NCD has decreased, diabetes would prevent Peru from meeting international targets. Policies are needed to prevent diabetes and to strengthen healthcare to avoid diabetes-related complications and delay mortality