You are here

  • Home
  • Archive
  • Volume 2, Issue 1
  • Addressing geographical variation in the progression of non-communicable diseases in Peru: the CRONICAS cohort study protocol

Article Text

Article menu

Download PDFPDF

XML
Epidemiology
Protocol
Addressing geographical variation in the progression of non-communicable diseases in Peru: the CRONICAS cohort study protocol
  1. J Jaime Miranda1,2,
  2. Antonio Bernabe-Ortiz1,3,
  3. Liam Smeeth1,4,
  4. Robert H Gilman1,5,6,
  5. William Checkley1,5,7,
  6. CRONICAS Cohort Study Group*
  1. 1CRONICAS Center of Excellence in Chronic Diseases, Universidad Peruana Cayetano Heredia, Lima, Peru
  2. 2Department of Medicine, School of Medicine, Universidad Peruana Cayetano Heredia, Lima, Peru
  3. 3Epidemiology Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru
  4. 4Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK
  5. 5Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, USA
  6. 6Área de Investigación y Desarrollo, Asociación Benéfica PRISMA, Lima, Peru
  7. 7Division of Pulmonary and Critical Care, School of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
  1. Correspondence to Dr J Jaime Miranda; jaime.miranda{at}upch.pe

Abstract

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.

This is an open-access article distributed under the terms of the Creative Commons Attribution Non-commercial License, which permits use, distribution, and reproduction in any medium, provided the original work is properly cited, the use is non commercial and is otherwise in compliance with the license. See: http://creativecommons.org/licenses/by-nc/2.0/ and http://creativecommons.org/licenses/by-nc/2.0/legalcode.

https://doi.org/10.1136/bmjopen-2011-000610

Statistics from Altmetric.com

    Request Permissions

    If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.

    Article summary

    Article focus

    • Compare prevalence and risk factors of cardiovascular and chronic obstructive pulmonary disease among three different populations.

    • Compare rate of disease progression to hypertension and diabetes from a disease-free baseline status between populations.

    • Compare rate of lung function decline between populations.

    Key messages

    • Our 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.

    Strengths and limitations of this study

    • The CRONICAS cohort is the first longitudinal study in Peru to assess cardiopulmonary risk factors among population from different geographical settings.

    Introduction

    In recent years, non-communicable diseases in low- and middle-income countries (LMIC) have received increasingly more global attention by scientists and by public health advocates and policy makers. Several publications underscore the high burden of disease associated with non-communicable diseases1–22 and its economic impact in LMIC.23–25 The topic has even reached to the higher political agenda at the United Nations in September 2011.26

    Whole determinants of many non-communicable diseases in LMIC are likely to be similar to those in affluent countries, yet population attributable fractions may differ due to differences in risk factor distributions.27 There is urgent need to better characterise current rates of non-communicable disease morbidity and mortality in LMIC to properly assess future projections.28 Most of the current approaches to understand non-communicable disease trends in LMIC are extrapolations of data obtained from high-income countries; however, since 80% of deaths related to non-communicable diseases occur in LMIC,2 generation of local knowledge to address such problems is needed. This has been recommended by WHO in its recent ‘Prioritised Research Agenda for Prevention and Control of Non-Communicable Diseases’.29

    Peru is a middle-income country where non-communicable diseases are responsible for 42% of total years of life lost30; however, mortality profiles are heterogeneous throughout the country and have rapidly shifted from a pattern dominated by infectious diseases to one dominated by non-communicable diseases and injuries over the last decade.31 As with other countries, cardiovascular disease (CVD) risk factors are strongly associated with lower socioeconomic status in Peru.32 33 Peru's diverse geography along with unequal societal development accounts for different stages of the epidemiological transition in different populations.34 35 In the same way, there is limited information about the burden of chronic obstructive pulmonary disease (COPD) in Peru. The PLATINO Study, which excluded Peru, found that the prevalence of COPD varied from 8% to 20% in individuals aged 40 years and older in five large Latin American cities, suggesting that COPD poses a considerable health burden in Latin America.36 Smoking was relatively prevalent (23%–29%) across the five cities included in PLATINO.37 In contrast, in Peru, we have recently found that overall rates of daily tobacco smoking are substantially lower than in other Latin American countries.38 However, other risk factors unique to LMIC such as biomass fuel exposure can contribute equally to the burden of COPD.39 40

    Understanding the effects of rapid urbanisation is one of the grand challenges concerning chronic non-communicable diseases.41 Peru offers a unique opportunity to assess the impact of geographical variation on non-communicable diseases.

    Methods

    Study design and settings

    The CRONICAS cohort is a longitudinal study that started in September 2010. This study is currently being performed in three settings in Peru (table 1). Pampas de San Juan de Miraflores is a periurban community located 25 km south of Lima's city centre, with approximately 60 000 people in about 4 km2, consisting mostly of Andean immigrants. This area is physically diverse and has experienced significant but unplanned population growth, with residents living on both low and high ground. The site in Tumbes is located in the northern coast of Peru and comprised by a group of communities with about 20 000 people spread over 80 km2, where the traditional agricultural landscape has become intermixed with rapidly growing urban sections. Puno is a city in southeastern Peru, located on the shore of Lake Titicaca. With a population of approximately 150 000 inhabitants, many villages surround the urban area. Use of biomass fuels is highly prevalent in these villages. Houses are made of adobe, and the majority does not have chimneys, with small windows kept closed, especially in the winter, due to the low temperatures at high altitudes.

    View this table:
    Table 1

    Characteristics of the CRONICAS Study settings

    Study objectives

    This study has the following objectives: to compare the (1) prevalence and risk factors of CVD and COPD, (2) rate of disease progression to hypertension and diabetes from a disease-free baseline status and (3) rate of lung function decline between populations.

    Participants and selection criteria

    All participants had to be aged 35 years and older, be a full-time resident in the area and be capable of understanding procedures and of providing informed consent. Participants who were pregnant, were cognitively incapable of providing informed consent or responding to a questionnaire, had any physical disability that would prevent measurements of anthropometrics and blood pressure and had active pulmonary tuberculosis were excluded. We enrolled only one participant per household.

    Fieldwork personnel selection and training

    Fieldwork personnel were trained in a course including modules on participant selection, human subjects protection and ethics, informed consent procedures, interviewing, clinical assessment and coding. The modules included formal lectures and demonstrations. Fieldworkers received a copy of an Interviewer's Manual. A team of approximately 30 field interviewers (10 per site) was selected. Additionally, a coordinator for each site was trained in this course. Thus, field personnel and coordinators were capable of conducting interviews and performing clinical assessments.

    Sampling method

    We identified a sex- and age-stratified random sample (35–44, 45–54, 55–64, ≥65 years of age) of potentially eligible subjects. We aimed to enrol 1000 subjects at each location. In Puno, we stratified recruitment to include 500 participants each from the urban and rural settings.

    Timeline: enrolment, baseline and follow-up visits

    Enrolment and baseline data collection started in September 2010. Follow-up visits will begin in February 2012 and an additional evaluation is planned to start in June 2013.

    At baseline, fieldworkers visited households to contact potential participants, verify inclusion and exclusion criteria, invite them to the study, read consent forms, apply questionnaires to participants and make an initial appointment for clinical evaluation. If potential participant was not found after three visits, a subject from the same age and sex group was randomly selected for replacement. The team had the responsibility to complete all clinical measurements and laboratory blood samples following standardised protocols. Recruitment of participants continued until the age- and sex-specific sample size was reached.

    Follow-up visits will be conducted at 20 and 40 months from enrolment. Sub-sections of the questionnaire as well as anthropometry, blood pressure and spirometry will be performed in all three visits. Blood sample collection will be undertaken only at baseline and at 40 months.

    Study procedures

    Questionnaires, informed consents, clinical forms and blood samples were labelled using alphanumeric codes to identify the site and participant.

    Questionnaires

    After informed consent was obtained, participants responded to a face-to-face questionnaire applied by a trained community health worker using paper-based formats. Data collected included several factors potentially associated with CVD and COPD, such as age, sex, years of education and other socioeconomic variables, smoking and alcohol habits, cardiovascular and respiratory symptoms, biomass fuel use and physical activity patterns. We used a modified version of WHO's STEP approach questionnaire for surveillance of non-communicable disease.42 Detailed information regarding sections and topics of the questionnaire is in table 2. In addition to the detailed survey, a rejection questionnaire comprising relevant questions to assure comparability between participants and non-responders was also applied to those who refuse to participate.

    View this table:
    Table 2

    Sections and topics of the questionnaire in the CRONICAS Study

    Phlebotomy and laboratory analyses

    A trained technician explained procedures for sample collection and then participants were asked to provide venous blood sample for specific tests (see table 3) in fasting conditions, at least 8 but <12 h. New appointments were scheduled if the fasting period was not appropriate. A total of 13.5 ml of blood were collected. Plasma glucose was measured using an enzymatic colorimetric method (GOD-PAP; Modular P-E/Roche-Cobas, Grenzach-Whylen, Germany), serum insulin using electrochemiluminescence (Modular P-E/Roche-Cobas), highly sensitive C reactive protein using Latex (Tina-quant CRP-HS Roche/Hitachi analyzer, Indianapolis, IN, USA) and haemoglobin A1C using high-performance liquid chromatography (D10, BioRad, Munich, Germany), which is traceable to the Diabetes Control and Complications Trial reference study as certified by the National Glycohemoglobin Standardisation Program. All samples were analysed in a single facility, and, for quality assurance, the quality of assays was checked with regular external standards and internal duplicate assays and monitored by BioRad (http://www.biorad.com). Information about sampling process is detailed in figure 1.

    View this table:
    Table 3

    Information about biological tests and sample type

    Figure 1
    Figure 1

    Flow chart of biological samples processing at laboratory.

    Clinical assessment

    We measured standing and sitting height, waist and hip circumference in triplicate using standardised techniques, heart rate, systolic and diastolic blood pressure were in triplicate using an automatic monitor OMRON HEM-780, previously validated for adult population.43 Ankle–brachial index, a marker of subclinical atherosclerosis that predicts the risk of future vascular events,44 was also measured using the same device. We measured weight and bioelectrical impedance using the TBF-300A body composition analyzer (TANITA Corporation, Tokyo, Japan). Measurements were carried out according to manufacturer's specifications.

    Spirometry

    We measured lung function using the Easy-On-PC spirometer (ndd, Zurich, Switzerland; http://www.ndd.ch). This device uses a flow metre that is not affected by changes in barometric pressure and therefore independent of gas density and suitable for use at high altitudes. We trained technicians to comply with the joint European Respiratory Society and American Thoracic Society guidelines.45 After training, three of the most skilful technicians were selected to perform procedures. In addition, we had a centralised quality control system in which all tests were graded according to standard guidelines46 to ensure that data collected is of highest quality. Regular calibration checks were performed. We also provided feedback to fieldworkers regarding spirometry activities. We recorded forced vital capacity (FVC), forced expiratory volume in one second (FEV1) as well as store individual flow–volume curves for quality control assessment and further analysis. All patients underwent bronchodilator-response testing. We administered two puffs from a salbutamol inhaler (100 mcg/puff) via a spacer and repeated spirometry 10–15 min later (a generic salbutamol inhaler was used for this project).

    We did not perform spirometry to any subject who had surgery of heart, chest, lungs or eyes in the past 3 months, or heart attack in the past 3 months, and a blood pressure greater than 180 (systolic) or 100 (diastolic). We did not use bronchodilators in participants with a heart rate >120 beats for minute. We rescheduled spirometry at a later date for participants who reported having a respiratory infection in the last 2 weeks, who had used a short-term bronchodilators in the last 4 h or a long-term bronchodilators in the last 12 h or who had smoked in the last hour.

    Measures of indoor air pollution

    In the second round of assessments, we plan to measure particulate matter (PM) in a random sample of 10% of households (100 per site) by placing PM monitors in the kitchen area. Average PM concentrations will be measured with the DataRAM pDR-1000 (Thermo Fisher Scientific, Waltham, Massachusetts, USA). We expect to collect PM data over a 48 h period. We will also assess aspects of household ventilation by measuring size of room and any windows or doors, as well as noting their state (open or closed) and the location of the kitchen and proximity to the living space. We will also record whether there is a fan in the room and if it was used during the 48 h of data collection.

    Study outcomes

    The primary outcomes for the baseline assessment are prevalence of major risk factors for cardiopulmonary diseases. The primary outcomes for the follow-up include longitudinal changes in blood pressure, blood glucose and lung function over 40 months. We will also able to assess traditional risk factors for CVD and COPD in all follow-up visits.

    Hypertension rates will be calculated using the average of the second and third blood pressure measures. Hypertension will be defined as the systolic blood pressure ≥140 mm Hg, and/or diastolic blood pressure ≥90 mm Hg, and/or self-report of current use of antihypertensive drugs.47 Diabetes mellitus will be defined as a fasting glucose ≥126 mg/dl (or ≥7 mmol/l) or self-report of physician diagnosis and currently receiving antidiabetic medication.48 As local references do not exist, we will define COPD as the presence of airflow limitation characterised by FEV1/FVC <70%.49 50 We will define reversibility as an improvement of >12% or >200 ml in baseline FEV1 or FVC in the post-salbutamol assessment.51

    Sample size and power

    Calculations for CVD outcomes were derived using prevalence estimates of hypertension from PERU MIGRANT Study.38 52 Prevalence in urban (Lima), migrant and rural groups was 30%, 13% and 12%, respectively. With 1000 people in each study site, the study would have power ≥80%, at the 5% significance level, to detect a 3% absolute difference in the prevalence of progression to hypertension between the sites over 4 years (ie, 8% will develop hypertension in Lima, 5% in Puno and 2% in Tumbes).

    To calculate the sample size for determining a difference in prevalence of COPD between site, we assume a prevalence ranging from 6% in Lima to 12% in Tumbes or Puno, with 5% significance and 90% power. We estimate a sample size of approximately 509 participants per site.

    Sample size calculations for lung function assessment over time included parameter and variances estimates from the UPLIFT trial,53 a 4-year study of tiotropium in COPD, using the following model:

    FEV1ijheightij2=β0+β1tij+b0i+b1itij+ɛij,bi∼N((00),(σ02σcσcσ12))andɛij∼N(0,σ2I).

    In this model, FEV1 is expressed in millilitres and height in metres. The outcome is equivalent to a height-adjusted FEV1. FEV1 is also affected by age, and this relationship is unlikely to be linear. However, we assume that the rate of decline over 40 months for each individual will be approximately linear. The values tij represents the jth measurement time for the ith participant. The βs are the regression parameters, and bi is the random effects. We used estimates obtained for male participants given that 75% of trial participants were male and that these estimates are likely to have the least amount of variability given the sample size of about 4000 participants. To calculate the sample size needed to detect a difference in our study from UPLIFT estimates, we used the following equation:nnew=SEβ12(UPLIFT)SEβ12(new)(LUPLIFTLnew)2nUPLIFT,where nnew is the sample size for our study; nUPLIFT is the sample size in UPLIFT trial; the SEs are the estimate of the SE for the expected β1 in our study and in UPLIFT, respectively and L is the follow-up duration in our study and in UPLIFT. Since we expect to follow all individuals for approximately 4 years, our study duration is similar to that of UPLIFT. We obtained the sex-stratified estimates from UPLIFT investigators.53 The SE for our study can be estimated as:SEβ1(new)=δβ1⌢Z(1−power)−Z(α),where δ is the per cent difference between sites, β1⌢ is the estimate of annual decline in FEV1 estimated from UPLIFT, Z(1-power) and Z(α) are the associated power and confidence level. Therefore, to detect a 50% change in the rate of decline in FEV1/height2 between sites with 5% significance and 90% power requires a total of 332 participants at each site followed longitudinally for 48 months. We assume that the rate of lung function decline for Tumbes will be similar to that of Lima. Assuming at 20% loss to follow-up, this would require approximately 400 participants. Even if we reduce the overall rate of decline in lung function by 25%, this would only increase the sample size requirement to 590 participants. Assuming at 20% loss to follow-up, this would require approximately 700 participants.

    Statistical methodology and analysis

    Following double data entry and careful data cleaning and consistency checking, descriptive statistics using tabulations and graphical methods will be performed. Direct standardisation to WHO standard population54 will be used to calculate age-standardised prevalences by specific age groups. Standardised mean differences, a unit-free comparison technique, will be used to evaluate the magnitude of difference between risk factors.55 56 The analysis will take into account the stratified nature of the sample at all stages and the repeated measures in individuals.

    Logistic regression (for binary outcomes) and multivariable linear regressions (for continuous normally distributed outcomes) will be used to assess the relationship between urbanisation and major cardiovascular and COPD risk factors. Appropriate longitudinal data methods will be used for the assessment of disease progression from baseline disease-free status to disease at follow-up. Multivariable models will look for risk factors that explain the relationship, such as blood pressure or fasting glucose when appropriate, body mass index, fasting total cholesterol, alcohol consumption, smoking status, regular exercise, income and other socioeconomic indicators as well as area of residence, will be pursued. Multilevel analysis to compare disease progression for site will be also considered.

    Ethical aspects

    This protocol and informed consent forms were approved with respect to scientific content and compliance with applicable research and human subjects' regulations. Protocol and consent forms were reviewed and approved by Institutional Review Boards at Universidad Peruana Cayetano Heredia and Johns Hopkins University.

    All investigators and personnel in the study have completed a training course in ethics and human subjects protection, certified by the National Institutes of Health. Informed consents were verbal because of sites included in this study were semi-urban and rural with significant rates of illiteracy; thus, interviewer signed the form to document participants' approval.

    Discussion

    This work emphasises the need of studies in different parts of the world, especially in LMIC to understand and assess non-communicable diseases and their risk factors. Peru is a very diverse country with different rates of urbanisation; thus, progression towards non-communicable conditions can vary widely from one geographical area to another. To our knowledge, two different cohorts are assessing non-communicable diseases in Latin America. The first one, the ELSA Study, a Brazilian cohort, has involved ‘white-collar’ volunteers to evaluate cardiovascular events.57 The second one, the CESCAS I Study, has started a cohort of participants focused in urban settings from Argentina, Chile and Uruguay to obtain CVD incidence using a multistage probabilistic sample.58

    The burden of non-communicable in LMIC is only expected to increase, yet limited data are available in these settings. Extrapolation of trends using data from high-income countries, where age profiles, risk factors and body composition differ, is unlikely to provide reasonable estimates or public health strategies to decrease disease burden. Generation of local knowledge to address such problems is needed to measure the magnitude of the problem, assess risk factors, which might be completely different from developed countries, and identify high-risk groups.59 The CRONICAS cohort has established a large cardiopulmonary cohort of adults, who will be followed-up over at least 4 years, with the possibility of longer term follow-ups and thus establishing itself as a unique resource arising from one LMIC in an area of major public health concern.

    There are several strengths that distinguish our study from other large-scale studies in Latin America. On the cardiovascular side, the assessment of risk using scores derived from developed countries has shown limitations in developing societies and may have limited application in settings like Peru. Determination of non-communicable disease epidemiology requires context-specific evaluation and follow-up of subjects over time, and this information is not available for Peru. On the pulmonary side, our study findings will complement that of BOLD and PLATINO as we will be able to provide an evaluation of longitudinal assessments of lung function across several settings according to degree of urbanisation, levels of outdoor and indoor air pollution and altitude. Specifically, our research will expand on the knowledge base of the epidemiology of lung function in LMIC with a high prevalence of biomass fuel exposure. Moreover, our data can also be used to generate local references for lung function among healthy, non-smoking non-biomass fuel-exposed adults, which currently do not exist for Peru. Most importantly, the uniqueness of geographical settings, the variety of stages of urbanisation, the long-term design of the study in an LMIC and the integration of cardiovascular- and pulmonary-related assessments will generate comprehensive data that will, in turn, provide important advances for public health and for the field of non-communicable diseases in LMIC.

    In Peru, according to WHO's 2011 non-communicable diseases country profile, there is no data regarding behavioural risk factors, especially in current daily tobacco smoking and physical inactivity prevalences.60 In addition, this report highlights the lack of an integrated policy programme for CVD, chronic respiratory diseases, diabetes, cancer, alcohol, tobacco, unhealthy diet, obesity and physical inactivity.60 Therefore, reducing the impact of non-communicable diseases will require alliances between different groups of research beyond national boundaries. With the support of the National Heart, Lung, and Blood Institute, we have the opportunity to establish initial steps towards an appropriate surveillance system for chronic diseases in Peru. The information gathered in this protocol will provide a strong platform to address potential interventions that are locally relevant and that could be applicable to other settings in Latin America, other LMIC and eventually potentially relevant for Latin population in the USA.

    Appendix 1 CRONICAS cohort study group (members listed in alphabetical order)

    Cardiovascular Disease: Antonio Bernabé-Ortiz, Juan P Casas, George Davey Smith, Shah Ebrahim, Raúl Gamboa, Héctor H García, Robert H Gilman, Luis Huicho, Germán Málaga, J Jaime Miranda, Víctor M Montori, Liam Smeeth; Chronic Obstructive Pulmonary Disease: William Checkley, Gregory B Diette, Robert H Gilman, Luis Huicho, Fabiola León-Velarde, María Rivera, Robert A Wise; Training & Capacity Building: William Checkley, Héctor H García, Robert H Gilman, J Jaime Miranda, Katherine Sacksteder.

    References

    1. ↵
      1. Adeyi O,
      2. Smith O,
      3. Robles S
      . Public Policy and the Challenge of Chronic Noncommunicable Diseases. Washington D.C: World Bank, 2007.
    2. ↵
      World Health Organization. Preventing Chronic Diseases: a Vital Investment. WHO Global Report. Geneva: World Health Organization, 2005.
    3. ↵
      1. Wang L,
      2. Kong L,
      3. Wu F,
      4. et al
      . Preventing chronic diseases in China. Lancet 2005;366:1821–4.
      OpenUrlCrossRefPubMedWeb of Science
    4. ↵
      1. Strong K,
      2. Mathers C,
      3. Leeder S,
      4. et al
      . Preventing chronic diseases: how many lives can we save? Lancet 2005;366:1578–82.
      OpenUrlCrossRefPubMedWeb of Science
    5. ↵
      1. Srinath Reddy K,
      2. Shah B,
      3. Varghese C,
      4. et al
      . Responding to the threat of chronic diseases in India. Lancet 2005;366:1744–9.
      OpenUrlCrossRefPubMedWeb of Science
    6. ↵
      1. Horton R
      . The neglected epidemic of chronic disease. Lancet 2005;366:1514.
      OpenUrlCrossRefPubMedWeb of Science
    7. ↵
      1. Epping-Jordan JE,
      2. Galea G,
      3. Tukuitonga C,
      4. et al
      . Preventing chronic diseases: taking stepwise action. Lancet 2005;366:1667–71.
      OpenUrlCrossRefPubMedWeb of Science
    8. ↵
      1. Lim SS,
      2. Gaziano TA,
      3. Gakidou E,
      4. et al
      . Prevention of cardiovascular disease in high-risk individuals in low-income and middle-income countries: health effects and costs. Lancet 2007;370:2054–62.
      OpenUrlCrossRefPubMedWeb of Science
    9. ↵
      1. Horton R
      . Chronic diseases: the case for urgent global action. Lancet 2007;370:1881–2.
      OpenUrlPubMedWeb of Science
    10. ↵
      1. Gaziano TA,
      2. Galea G,
      3. Reddy KS
      . Scaling up interventions for chronic disease prevention: the evidence. Lancet 2007;370:1939–46.
      OpenUrlCrossRefPubMedWeb of Science
    11. ↵
      1. Beaglehole R,
      2. Ebrahim S,
      3. Reddy S,
      4. et al
      . Prevention of chronic diseases: a call to action. Lancet 2007;370:2152–7.
      OpenUrlCrossRefPubMedWeb of Science
    12. ↵
      1. Abegunde DO,
      2. Mathers CD,
      3. Adam T,
      4. et al
      . The burden and costs of chronic diseases in low-income and middle-income countries. Lancet 2007;370:1929–38.
      OpenUrlCrossRefPubMedWeb of Science
    13. ↵
      1. Samb B,
      2. Desai N,
      3. Nishtar S,
      4. et al
      . Prevention and management of chronic disease: a litmus test for health-systems strengthening in low-income and middle-income countries. Lancet 2011;376:1785–97.
      OpenUrlWeb of Science
    14. ↵
      1. Mbanya JC,
      2. Squire SB,
      3. Cazap E,
      4. et al
      . Mobilising the world for chronic NCDs. Lancet 2011;377:536–7.
      OpenUrlCrossRefPubMedWeb of Science
    15. ↵
      1. Geneau R,
      2. Stuckler D,
      3. Stachenko S,
      4. et al
      . Raising the priority of preventing chronic diseases: a political process. Lancet 2011;376:1689–98.
      OpenUrlWeb of Science
    16. ↵
      1. Beaglehole R,
      2. Horton R
      . Chronic diseases: global action must match global evidence. Lancet 2011;376:1619–21.
      OpenUrlWeb of Science
    17. ↵
      1. Beaglehole R,
      2. Bonita R,
      3. Horton R,
      4. et al
      . Priority actions for the non-communicable disease crisis. Lancet 2011;377:1438–47.
      OpenUrlCrossRefPubMedWeb of Science
    18. ↵
      1. Alwan A,
      2. Maclean DR,
      3. Riley LM,
      4. et al
      . Monitoring and surveillance of chronic non-communicable diseases: progress and capacity in high-burden countries. Lancet 2011;376:1861–8.
      OpenUrlWeb of Science
    19. ↵
      1. Anderson GF,
      2. Chu E
      . Expanding priorities–confronting chronic disease in countries with low income. N Engl J Med 2007;356:209–11.
      OpenUrlCrossRefPubMedWeb of Science
    20. ↵
      1. Ebrahim S,
      2. Smeeth L
      . Non-communicable diseases in low and middle-income countries: a priority or a distraction? Int J Epidemiol 2005;34:961–6.
      OpenUrlFREE Full Text
    21. ↵
      1. Perel P,
      2. Casas JP,
      3. Ortiz Z,
      4. et al
      . Noncommunicable diseases and injuries in Latin America and the Caribbean: time for action. PLoS Med 2006;3:e344.
      OpenUrlCrossRefPubMed
    22. ↵
      1. Yusuf S,
      2. Reddy S,
      3. Ounpuu S,
      4. et al
      . Global burden of cardiovascular diseases: part I: general considerations, the epidemiologic transition, risk factors, and impact of urbanisation. Circulation 2001;104:2746–53.
      OpenUrlAbstract/FREE Full Text
    23. ↵
      1. Bloom DE,
      2. Cafiero ET,
      3. Jané-Llopis E,
      4. et al
      . The Global Economic Burden of Non-Communicable Diseases. Geneva: World Economic Forum, 2011.
    24. ↵
      1. Suhrcke M,
      2. Nugent RA,
      3. Stuckler D,
      4. et al
      . Chronic disease: An Economic Perspective. London: Oxford Health Alliance, 2006.
    25. ↵
      1. Leeder S,
      2. Raymond S,
      3. Greenberg H,
      4. et al
      . A Race against Time: The Challenge of Cardiovascular Disease in Developing Economies. New York: The Earth Institute, Columbia University, 2004.
    26. ↵
      1. Cerqueira MT,
      2. Cravioto A,
      3. Dianis N,
      4. et al
      . Global response to non-communicable disease. BMJ 2011;342:d3823.
      OpenUrlFREE Full Text
    27. ↵
      1. Yusuf S,
      2. Hawken S,
      3. Ounpuu S,
      4. et al
      . Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case-control study. Lancet 2004;364:937–52.
      OpenUrlCrossRefPubMedWeb of Science
    28. ↵
      1. Yusuf S,
      2. Vaz M,
      3. Pais P
      . Tackling the challenge of cardiovascular disease burden in developing countries. Am Heart J 2004;148:1–4.
      OpenUrlCrossRefPubMedWeb of Science
    29. ↵
      World Health Organization. Prioritized Research Agenda for Prevention and Control of Noncommunicable Diseases. Geneva, Switzerland: World Health Organization, 2008.
    30. ↵
      1. Perel P,
      2. Miranda JJ,
      3. Ortiz Z,
      4. et al
      . Relation between the global burden of disease and randomized clinical trials conducted in Latin America published in the five leading medical journals. PLoS One 2008;3:e1696.
      OpenUrlCrossRefPubMed
    31. ↵
      PAHO-Peru. Health in Americas—2007 Edition. Washington D.C: PAHO, 2007.
    32. ↵
      1. Jacoby E,
      2. Goldstein J,
      3. Lopez A,
      4. et al
      . Social class, family, and life-style factors associated with overweight and obesity among adults in Peruvian cities. Prev Med 2003;37:396–405.
      OpenUrlCrossRefPubMedWeb of Science
    33. ↵
      1. Medina-Lezama J,
      2. Zea-Diaz H,
      3. Morey-Vargas OL,
      4. et al
      . Prevalence of the metabolic syndrome in Peruvian Andean hispanics: the PREVENCION study. Diabetes Res Clin Pract 2007;78:270–81.
      OpenUrlPubMed
    34. ↵
      1. Goldstein J,
      2. Jacoby E,
      3. del Aguila R,
      4. et al
      . Poverty is a predictor of non-communicable disease among adults in Peruvian cities. Prev Med 2005;41:800–6.
      OpenUrlCrossRefPubMedWeb of Science
    35. ↵
      1. Yusuf S,
      2. Ounpuu S
      . Tackling the growing global burden of atherosclerotic cardiovascular diseases. Eur J Cardiovasc Prev Rehabil 2003;10:236–9.
      OpenUrlFREE Full Text
    36. ↵
      1. Menezes AM,
      2. Perez-Padilla R,
      3. Jardim JR,
      4. et al
      . Chronic obstructive pulmonary disease in five Latin American cities (the PLATINO study): a prevalence study. Lancet 2005;366:1875–81.
      OpenUrlCrossRefPubMedWeb of Science
    37. ↵
      1. Menezes AM,
      2. Lopez MV,
      3. Hallal PC,
      4. et al
      . Prevalence of smoking and incidence of initiation in the Latin American adult population: the PLATINO study. BMC Public Health 2009;9:151.
      OpenUrlCrossRefPubMed
    38. ↵
      1. Miranda JJ,
      2. Gilman RH,
      3. Smeeth L
      . Differences in cardiovascular risk factors in rural, urban and rural-to-urban migrants in Peru. Heart 2011;97:787–96.
      OpenUrlAbstract/FREE Full Text
    39. ↵
      1. Buist AS,
      2. McBurnie MA,
      3. Vollmer WM,
      4. et al
      . International variation in the prevalence of COPD (the BOLD Study): a population-based prevalence study. Lancet 2007;370:741–50.
      OpenUrlCrossRefPubMedWeb of Science
    40. ↵
      1. Torres-Duque C,
      2. Maldonado D,
      3. Perez-Padilla R,
      4. et al
      . Biomass fuels and respiratory diseases: a review of the evidence. Proc Am Thorac Soc 2008;5:577–90.
      OpenUrlCrossRefPubMed
    41. ↵
      1. Daar AS,
      2. Singer PA,
      3. Persad DL,
      4. et al
      . Grand challenges in chronic non-communicable diseases. Nature 2007;450:494–6.
      OpenUrlCrossRefPubMedWeb of Science
    42. ↵
      World Health Organization. WHO STEPwise Approach to Surveillance (STEPS). STEPS Manual. Geneva, Switzerland. http://www.who.int/chp/steps/manual/en/index.html
    43. ↵
      1. Coleman A,
      2. Steel S,
      3. Freeman P,
      4. et al
      . Validation of the Omron M7 (HEM-780-E) oscillometric blood pressure monitoring device according to the British Hypertension Society protocol. Blood Pressure Monit 2008;13:49–54.
      OpenUrlCrossRefPubMedWeb of Science
    44. ↵
      1. Heald CL,
      2. Fowkes FG,
      3. Murray GD,
      4. et al
      . Risk of mortality and cardiovascular disease associated with the ankle-brachial index: systematic review. Atherosclerosis 2006;189:61–9.
      OpenUrlCrossRefPubMedWeb of Science
    45. ↵
      1. Miller MR,
      2. Hankinson J,
      3. Brusasco V,
      4. et al
      . Standardisation of spirometry. Eur Respir J 2005;26:319–38.
      OpenUrlAbstract/FREE Full Text
    46. ↵
      1. Ferguson GT,
      2. Enright PL,
      3. Buist AS,
      4. et al
      . Office spirometry for lung health assessment in adults: a consensus statement from the National Lung Health Education Program. Chest 2000;117:1146–61.
      OpenUrlCrossRefPubMedWeb of Science
    47. ↵
      1. Chobanian AV,
      2. Bakris GL,
      3. Black HR,
      4. et al
      . Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure. Hypertension 2003;42:1206–52.
      OpenUrlAbstract/FREE Full Text
    48. ↵
      Report of the expert committee on the diagnosis and classification of diabetes mellitus. Diabetes Care 2003;26(Suppl 1):S5–20.
      OpenUrlCrossRefPubMedWeb of Science
    49. ↵
      1. Lamprecht B,
      2. Schirnhofer L,
      3. Kaiser B,
      4. et al
      . Subjects with discordant airways obstruction: lost between spirometric definitions of COPD. Pulm Med 2011;2011:780215.
      OpenUrlPubMed
    50. ↵
      Global Initiative for Chronic Obstructive Lung Disease (GOLD). http://www.goldcopd.org (accessed 30 Sep 2011).
    51. ↵
      1. Miller MR,
      2. Hankinson J,
      3. Brusasco V,
      4. et al
      ; ATS/ERS Task Force. Standardisation of spirometry. Eur Respir J 2005;26:319–38.
      OpenUrlAbstract/FREE Full Text
    52. ↵
      1. Miranda JJ,
      2. Gilman RH,
      3. Garcia HH,
      4. et al
      . The effect on cardiovascular risk factors of migration from rural to urban areas in Peru: PERU MIGRANT study. BMC Cardiovasc Disord 2009;9:23.
      OpenUrlCrossRefPubMed
    53. ↵
      1. Morice AH,
      2. Celli B,
      3. Kesten S,
      4. et al
      . COPD in young patients: a pre-specified analysis of the four-year trial of tiotropium (UPLIFT). Respir Med 2010;104:1659–67.
      OpenUrlCrossRefPubMed
    54. ↵
      World Health Organization. The WHO Standard Population. Geneva: World Health Organization. https://apps.who.int/infobase/help.aspx?helpid=293
    55. ↵
      1. Cohen J
      . Statistical Power Analysis in the Behavioral Sciences. 2nd edn. Hillsdale, NJ: Lawrence Erlbaum Associates, Inc., 1988.
    56. ↵
      1. Higgins JPT,
      2. Green S
      , eds. Cochrane Handbook for Systematic Reviews of Interventions. Version 5.1.0. The Cochrane Collaboration, 2011. Available from www.cochrane-handbook.org
    57. ↵
      Departamento de Ciência e Tecnologia, Secretaria de Ciência, Tecnologia e Insumos Estratégicos, Ministério da Saúde. ELSA Brasil: the greatest epidemiological study in Latin America [In Portuguese]. Rev Saude Publica. 2009 Feb;43(1).10.1590/S0034-89102009000100028. http://www.scielosp.org/scielo.php?script=sci_isoref&pid=S0034-89102009000100028&lng=en&tlng=pt.
    58. ↵
      1. Rubinstein A,
      2. Irazola V,
      3. Poggio R,
      4. et al
      . Detection and follow-up of cardiovascular disease and risk factors in the Southern Cone of Latin America: the CESCAS I study. BMJ Open 2011;1:e000126.
      OpenUrlAbstract/FREE Full Text
    59. ↵
      1. Narayan KM,
      2. Ali MK,
      3. del Rio C,
      4. et al
      . Global noncommunicable diseases–lessons from the HIV-AIDS experience. N Engl J Med 2011;365:876–8.
      OpenUrlCrossRefPubMedWeb of Science
    60. ↵
      Noncommunicable Diseases Country Profile 2011-WHO Global Report. Geneva, Switzerland: WHO, 2011.

    Footnotes

    • ↵* Members of the CRONICAS Cohort Study Group listed in appendix 1.

    • To cite: Miranda JJ, Bernabe-Ortiz A, Smeeth L, et al. Addressing geographical variation in the progression of non-communicable diseases in Peru: the CRONICAS cohort study protocol. BMJ Open 2012;2:e000610. doi:10.1136/bmjopen-2011-000610

    • Funding This study was supported by the National Heart, Lung, and Blood Institute Global Health Initiative under the contract Global Health Activities in Developing Countries to Combat Non-Communicable Chronic Diseases (project number 268200900033C-1-0-1). Study design; collection, management, analysis and interpretation of data; writing of the report and the decision to submit the report for publication will be/are all independent of the funders. Ultimate authority for these activities will lie with principal investigators.

    • Competing interests None.

    • Patient consent Obtained.

    • Contributors JJM and AB-O drafted the first version of the manuscript. JJM, LS, RHG and WC conceived, designed and supervised the overall study. All authors participated in writing of the manuscript, provided important intellectual content and gave their final approval of the version submitted for publication.

    • Provenance and peer review Not commissioned; internally peer reviewed.