Geographical variation in the progression of type 2 diabetes in Peru: The CRONICAS Cohort Study.

BACKGROUND: The study aims were to estimate the incidence and risk factors for T2D in four settings with different degree of urbanization and altitude in Peru. METHODS: Prospective cohort study conducted in urban, semi-urban, and rural areas in Peru. An age- and sex-stratified random sample of participants was taken from the most updated census. T2D was defined as fasting blood glucose ⩾7.0mmol/L or taking anti-diabetes medication. Exposures were divided into two groups: geographical variables (urbanization and altitude), and modifiable risk factors. Incidence, relative risks (RR), 95% confidence intervals (95%CI), and population attributable fractions (PAF) were estimated. RESULTS: Data from 3135 participants, 48.8% males, mean age 55.6years, was analyzed. Overall baseline prevalence of T2D was 7.1% (95%CI 6.2-8.0%). At follow-up, including 6207 person-years of follow-up, a total of 121 new T2D cases were accrued, equating to an incidence of 1.95 (95%CI 1.63-2.33) per 100 person-years. There was no urban to rural gradient in the T2D incidence; however, compared to sea level sites, participants living in high altitude had a higher incidence of diabetes (RR=1.58; 95%CI 1.01-2.48). Obesity had the highest attributable risk for developing T2D, although results varied by setting, ranging from 14% to 80% depending on urbanization and altitude. CONCLUSIONS: Our results suggest that the incidence of T2D was greater in high altitude sites. New cases of diabetes were largely attributed to obesity, but with substantial variation in the contribution of obesity depending on the environment. These findings can inform appropriate context-specific strategies to reduce the incidence of diabetes

Trajectories of body mass index and waist circumference in four Peruvian settings at different level of urbanisation: the CRONICAS Cohort Study

BACKGROUND: Studies have reported the incidence/risk of becoming obese, but few have described the trajectories of body mass index (BMI) and waist circumference (WC) over time, especially in low/middle-income countries. We assessed the trajectories of BMI and WC according to sex in four sites in Peru. METHODS: Data from the population-based CRONICAS Cohort Study were analysed. We fitted a population-averaged model by using generalised estimating equations. The outcomes of interest, with three data points over time, were BMI and WC. The exposure variable was the factorial interaction between time and study site. RESULTS: At baseline mean age was 55.7 years (SD: 12.7) and 51.6% were women. Mean follow-up time was 2.5 years (SD: 0.4). Over time and across sites, BMI and WC increased linearly. The less urbanised sites showed a faster increase than more urbanised sites, and this was also observed after sex stratification. Overall, the fastest increase was found for WC compared with BMI. Compared with Lima, the fastest increase in WC was in rural Puno (coefficient=0.73, P<0.001), followed by urban Puno (coefficient=0.59, P=0.001) and Tumbes (coefficient=0.22, P=0.088). CONCLUSIONS: There was a linear increase in BMI and WC across study sites, with the greatest increase in less urbanised areas. The ongoing urbanisation process, common to Peru and other low/middle-income countries, is accompanied by different trajectories of increasing obesity-related markers

Addressing geographical variation in the progression of non-communicable diseases in Peru: the CRONICAS cohort study protocol

Background The rise in non-communicable diseases in developing countries has gained increased attention. Given that around 80% of deaths related to non-communicable diseases occur in low- and middle-income countries, there is a need for local knowledge to address such problems. Longitudinal studies can provide valuable information about disease burden of non-communicable diseases in Latin America to inform both public health and clinical settings. Methods The CRONICAS cohort is a longitudinal study performed in three Peruvian settings that differ by degree of urbanisation, level of outdoor and indoor pollution and altitude. The author sought to enrol an age- and sex-stratified random sample of 1000 participants at each site. Study procedures include questionnaires on socio-demographics and well-known risk factors for cardiopulmonary disease, blood draw, anthropometry and body composition, blood pressure and spirometry before and after bronchodilators. All participants will be visited at baseline, at 20 and 40 months. A random sample of 100 households at each site will be assessed for 24 h particulate matter concentration. Primary outcomes include prevalence of risk factors for cardiopulmonary diseases, changes in blood pressure and blood glucose over time and decline in lung function. Discussion There is an urgent need to characterise the prevalence and burden of non-communicable diseases in low- and middle-income countries. Peru is a middle-income country currently undergoing a rapid epidemiological transition. This longitudinal study will provide valuable information on cardiopulmonary outcomes in three different settings and will provide a platform to address potential interventions that are locally relevant or applicable to other similar settings in Latin America

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

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

Development and Validation of a Simple Risk Score for Undiagnosed Type 2 Diabetes in a Resource-Constrained Setting.

Objective. To develop and validate a risk score for detecting cases of undiagnosed diabetes in a resource-constrained country. Methods. Two population-based studies in Peruvian population aged ≥35 years were used in the analysis: the ENINBSC survey (n = 2,472) and the CRONICAS Cohort Study (n = 2,945). Fasting plasma glucose ≥7.0 mmol/L was used to diagnose diabetes in both studies. Coefficients for risk score were derived from the ENINBSC data and then the performance was validated using both baseline and follow-up data of the CRONICAS Cohort Study. Results. The prevalence of undiagnosed diabetes was 2.0% in the ENINBSC survey and 2.9% in the CRONICAS Cohort Study. Predictors of undiagnosed diabetes were age, diabetes in first-degree relatives, and waist circumference. Score values ranged from 0 to 4, with an optimal cutoff ≥2 and had a moderate performance when applied in the CRONICAS baseline data (AUC = 0.68; 95% CI: 0.62-0.73; sensitivity 70%; specificity 59%). When predicting incident cases, the AUC was 0.66 (95% CI: 0.61-0.71), with a sensitivity of 69% and specificity of 59%. Conclusions. A simple nonblood based risk score based on age, diabetes in first-degree relatives, and waist circumference can be used as a simple screening tool for undiagnosed and incident cases of diabetes in Peru

Metabolic Abnormalities Are Common among South American Hispanics Subjects with Normal Weight or Excess Body Weight: The CRONICAS Cohort Study.

OBJECTIVE: We aimed to characterize metabolic status by body mass index (BMI) status. METHODS: The CRONICAS longitudinal study was performed in an age-and-sex stratified random sample of participants aged 35 years or older in four Peruvian settings: Lima (Peru's capital, costal urban, highly urbanized), urban and rural Puno (both high-altitude), and Tumbes (costal semirural). Data from the baseline study, conducted in 2010, was used. Individuals were classified by BMI as normal weight (18.5-24.9 kg/m2), overweight (25.0-29.9 kg/m2), and obese (≥30 kg/m2), and as metabolically healthy (0-1 metabolic abnormality) or metabolically unhealthy (≥2 abnormalities). Abnormalities included individual components of the metabolic syndrome, high-sensitivity C-reactive protein, and insulin resistance. RESULTS: A total of 3088 (age 55.6±12.6 years, 51.3% females) had all measurements. Of these, 890 (28.8%), 1361 (44.1%) and 837 (27.1%) were normal weight, overweight and obese, respectively. Overall, 19.0% of normal weight in contrast to 54.9% of overweight and 77.7% of obese individuals had ≥3 risk factors (p<0.001). Among normal weight individuals, 43.1% were metabolically unhealthy, and age ≥65 years, female, and highest socioeconomic groups were more likely to have this pattern. In contrast, only 16.4% of overweight and 3.9% of obese individuals were metabolically healthy and, compared to Lima, the rural and urban sites in Puno were more likely to have a metabolically healthier profile. CONCLUSIONS: Most Peruvians with overweight and obesity have additional risk factors for cardiovascular disease, as well as a majority of those with a healthy weight. Prevention programs aimed at individuals with a normal BMI, and those who are overweight and obese, are urgently needed, such as screening for elevated fasting cholesterol and glucose

Urbanization, mainly rurality, but not altitude is associated with dyslipidemia profiles.

BACKGROUND: Geographical and environmental features such as urbanization and altitude may influence individual's lipid profiles because of the diversity of human-environment interactions including lifestyles. OBJECTIVE: To characterize the association between altitude and urbanization and lipid profile among Peruvian adults aged ≥35 years. METHODS: Cross-sectional analysis of the CRONICAS Cohort Study. The outcomes of interest were 6 dyslipidemia traits: hypertriglyceridemia, high low-density lipoprotein cholesterol, low high-density lipoprotein cholesterol (HDL-c), nonisolated low HDL-c, isolated low HDL-c, and high non-HDL-c. The exposures of interest were urbanization level (highly urban, urban, semi-urban, and rural) and altitude (high altitude vs sea level). Prevalence ratios (PRs) and 95% confidence intervals (95% CIs) were calculated using Poisson regression models with robust variance adjusting for potential confounders. RESULTS: Data from 3037 individuals, 48.5% males, mean age of 55.6 (standard deviation ±12.7) years, were analyzed. The most common dyslipidemia pattern was high non-HDL-c with a prevalence of 88.0% (95% CI: 84.9%-90.7%) in the rural area and 96.0% (95% CI: 94.5%-97.1%) in the semi-urban area. Relative to the highly urban area, living in rural areas was associated with a lower prevalence of hypertriglyceridemia (PR = 0.75; 95% CI: 0.56-0.99) and high non-HDL-c (PR = 0.96; 95% CI: 0.93-0.99), whereas living in semi-urban areas was associated with higher prevalence high low-density lipoprotein cholesterol (PR = 1.37; 95% CI: 1.11-1.67). Compared with sea level areas, high-altitude areas had lower prevalence of high non-HDL-c (PR = 0.97; 95% CI: 0.95-0.99). CONCLUSION: Urbanization but not altitude was associated to several dyslipidemia traits, with the exception of high non-HDL-c in high altitude settings

Risk score for first-screening of prevalent undiagnosed chronic kidney disease in Peru: the CRONICAS-CKD risk score.

BACKGROUND: Chronic Kidney Disease (CKD) represents a great burden for the patient and the health system, particularly if diagnosed at late stages. Consequently, tools to identify patients at high risk of having CKD are needed, particularly in limited-resources settings where laboratory facilities are scarce. This study aimed to develop a risk score for prevalent undiagnosed CKD using data from four settings in Peru: a complete risk score including all associated risk factors and another excluding laboratory-based variables. METHODS: Cross-sectional study. We used two population-based studies: one for developing and internal validation (CRONICAS), and another (PREVENCION) for external validation. Risk factors included clinical- and laboratory-based variables, among others: sex, age, hypertension and obesity; and lipid profile, anemia and glucose metabolism. The outcome was undiagnosed CKD: eGFR < 60 ml/min/1.73m2. We tested the performance of the risk scores using the area under the receiver operating characteristic (ROC) curve, sensitivity, specificity, positive/negative predictive values and positive/negative likelihood ratios. RESULTS: Participants in both studies averaged 57.7 years old, and over 50% were females. Age, hypertension and anemia were strongly associated with undiagnosed CKD. In the external validation, at a cut-off point of 2, the complete and laboratory-free risk scores performed similarly well with a ROC area of 76.2% and 76.0%, respectively (P = 0.784). The best assessment parameter of these risk scores was their negative predictive value: 99.1% and 99.0% for the complete and laboratory-free, respectively. CONCLUSIONS: The developed risk scores showed a moderate performance as a screening test. People with a score of ≥ 2 points should undergo further testing to rule out CKD. Using the laboratory-free risk score is a practical approach in developing countries where laboratories are not readily available and undiagnosed CKD has significant morbidity and mortality

The HOMA-IR performance to identify new diabetes cases by degree of urbanization and altitude in Peru: The CRONICAS Cohort Study

Aims. Prognostic thresholds to identify new type 2 diabetes mellitus (T2DM) cases using the HOMA-IR have not been defined. We studied the HOMA-IR performance to identify incident T2DM cases and to assess if the thresholds varied according to urbanization and altitude in Peru. Methods. Longitudinal analysis. The outcome was incident T2DM cases: self-report diagnosis and fasting glucose. The exposure was the HOMA-IR. Receiver operating characteristic (ROC) curves were plotted, and the area under the ROC curve (AUC) was estimated with 95% confidence intervals (95% CIs). Results are presented overall and stratified by study site (Lima, Tumbes, urban Puno, and rural Puno), rurality (urban, semiurban, and rural), and altitude (low and high). Results. A total of 3120 participants (mean age: 55.6 years, 51.2% females) contributed data to this analysis. The median baseline HOMA-IR was 1.7 (IQR 1.0–2.9), with median values ranging from 1.1 in rural Puno to 2.0 in Lima and Tumbes (). Overall for incident T2DM, the AUC was 0.69 (95% CI: 0.64–0.74) with an empirical threshold of 2.8 yielding a positive likelihood ratio of 2.30 and a negative one of 0.61; the positive and negative predictive values were 14.6% and 95.7%, respectively. The empirical thresholds varied within the variables of interest, for example, from 0.9 in urban Puno to 2.9 in Lima. Conclusions. Using the HOMA-IR to identify incident T2DM cases seems to yield moderate accuracy. The HOMA-IR could help improve identifying people at high risk of T2DM