Dataset Information

Addressing the impact of urban exposure on the incidence of type 2 diabetes mellitus: The PERU MIGRANT Study.

ABSTRACT: The aim of this study was to estimate the incidence of T2DM in three population groups: rural, rural-to-urban migrants and urban dwellers. Data from the PERU MIGRANT Study was analysed. The baseline assessment was conducted in 2007-2008 using a single-stage random sample and further follow-up was undertaken in 2015-16. T2DM was defined based on fasting glucose and self-reported diagnosis. Poisson regression models and robust variance to account for cluster effects were used for reporting risk ratios (RR) and 95%CI. At baseline, T2DM prevalence was 8% in urban, 3.6% in rural-to-urban migrants and 1.5% in rural dwellers. After 7.7 (SD: 1.1) years, 6,076 person-years of follow-up, 61 new cases were identified. The incidence rates in the urban, migrant and rural groups were 1.6, 0.9 and 0.5 per 100 person-years, respectively. Relative to rural dwellers, a 4.3-fold higher risk (95%CI: 1.6-11.9) for developing T2DM was found in urban dwellers and 2.7-fold higher (95%CI: 1.1-6.8) in migrants with ?30 years of urban exposure. Migration and urban exposure were found as significant risk factors for developing T2DM. Within-country migration is a sociodemographic phenomenon occurring worldwide; thus, it is necessary to disentangle the effect of urban exposure on non-healthy habits and T2DM development.

SUBMITTER: Ruiz-Alejos A

PROVIDER: S-EPMC5883030 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

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Addressing the impact of urban exposure on the incidence of type 2 diabetes mellitus: The PERU MIGRANT Study.

Ruiz-Alejos Andrea A Carrillo-Larco Rodrigo M RM Miranda J Jaime JJ Anderson Cheryl A M CAM Gilman Robert H RH Smeeth Liam L Bernabé-Ortiz Antonio A

Scientific reports 20180403 1

The aim of this study was to estimate the incidence of T2DM in three population groups: rural, rural-to-urban migrants and urban dwellers. Data from the PERU MIGRANT Study was analysed. The baseline assessment was conducted in 2007-2008 using a single-stage random sample and further follow-up was undertaken in 2015-16. T2DM was defined based on fasting glucose and self-reported diagnosis. Poisson regression models and robust variance to account for cluster effects were used for reporting risk ra ...[more]

PMID: 29615740

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Project description:Mass-migration observed in Peru from the 1970s occurred because of the need to escape from politically motivated violence and work related reasons. The majority of the migrant population, mostly Andean peasants from the mountainous areas, tends to settle in clusters in certain parts of the capital and their rural environment could not be more different than the urban one. Because the key driver for migration was not the usual economic and work-related reasons, the selection effects whereby migrants differ from non-migrants are likely to be less prominent in Peru. Thus the Peruvian context offers a unique opportunity to test the effects of migration.The PERU MIGRANT (PEru's Rural to Urban MIGRANTs) study was designed to investigate the magnitude of differences between rural-to-urban migrant and non-migrant groups in specific CVD risk factors. For this, three groups were selected: Rural, people who have always have lived in a rural environment; Rural-urban, people who migrated from rural to urban areas; and, Urban, people who have always lived in a urban environment.Overall response rate at enrolment was 73.2% and overall response rate at completion of the study was 61.6%. A rejection form was obtained in 282/323 people who refused to take part in the study (87.3%). Refusals did not differ by sex in rural and migrant groups, but 70% of refusals in the urban group were males. In terms of age, most refusals were observed in the oldest age-group (>60 years old) in all study groups. The final total sample size achieved was 98.9% of the target sample size (989/1000). Of these, 52.8% (522/989) were females. Final size of the rural, migrant and urban study groups were 201, 589 and 199 urban people, respectively. Migrant's average age at first migration and years lived in an urban environment were 14.4 years (IQR 10-17) and 32 years (IQR 25-39), respectively. This paper describes the PERU MIGRANT study design together with a critical analysis of the potential for bias and confounding in migrant studies, and strategies for reducing these problems. A discussion of the potential advantages provided by the case of migration in Peru to the field of migration and health is also presented.

Project description:BackgroundAlthough migration and urbanization have been linked with higher obesity rates, especially in low-resource settings, prospective information about the magnitude of these effects is lacking. We estimated the risk of obesity and central obesity among rural subjects, rural-to-urban migrants and urban subjects.MethodsProspective data from the PERU MIGRANT Study were analyzed. Baseline data were collected in 2007-2008 and participants re-contacted in 2012-2013. At follow-up, outcomes were obesity and central obesity measured by body mass index and waist circumference. At baseline, the primary exposure was demographic group: rural, rural-to-urban migrant and urban. Other exposures included an assets index and educational attainment. Cumulative incidence, incidence ratio (IR) and 95% confidence intervals (95% CI) for obesity and central obesity were estimated with Poisson regression models.ResultsAt baseline, mean age (±s.d.) was 47.9 (±12.0) years, and 53.0% were females. Rural subjects comprised 20.2% of the total sample, whereas 59.7% were rural-to-urban migrants and 20.1% were urban dwellers. A total of 3598 and 2174 person-years were analyzed for obesity and central obesity outcomes, respectively. At baseline, the prevalence of obesity and central obesity was 20.0 and 52.5%. In multivariable models, migrant and urban groups had an 8- to 9.5-fold higher IR of obesity compared with the rural group (IR migrants=8.19, 95% CI=2.72-24.67; IR urban=9.51, 95% CI=2.74-33.01). For central obesity, there was a higher IR only among the migrant group (IR=1.95; 95% CI=1.22-3.13). Assets index was associated with a higher IR of central obesity (IR top versus bottom tertile 1.45, 95% CI=1.03-2.06).ConclusionsPeruvian urban individuals and rural-to-urban migrants show a higher incidence of obesity compared with their rural counterparts. Given the ongoing urbanization occurring in middle-income countries, the rapid development of increased obesity risk by rural-to-urban migrants suggests that measures to reduce obesity should be a priority for this group.

Project description:BACKGROUND: Sub-Saharan Africa faces a rapid spread of diabetes mellitus type 2 (DM2) but its potentially specific characteristics are inadequately defined. In this hospital-based study in Kumasi, Ghana, we aimed at characterizing clinical, anthropometric, socio-economic, nutritional and behavioural parameters of DM2 patients and at identifying associated factors. METHODS: Between August 2007 and June 2008, 1466 individuals were recruited from diabetes and hypertension clinics, outpatients, community, and hospital staff. Fasting plasma glucose (FPG), serum lipids and urinary albumin were measured. Physical examination, anthropometry, and interviews on medical history, socio-economic status (SES), physical activity and nutritional behaviour were performed. RESULTS: The majority of the 675 DM2 patients (mean FPG, 8.31 mmol/L) was female (75%) and aged 40-60 years (mean, 55 years). DM2 was known in 97% of patients, almost all were on medication. Many had hypertension (63%) and microalbuminuria (43%); diabetic complications occurred in 20%. Overweight (body mass index > 25 kg/m2), increased body fat (> 20% (male), > 33% (female)), and central adiposity (waist-to-hip ratio > 0.90 (male), > 0.85 (female)) were frequent occurring in 53%, 56%, and 75%, respectively. Triglycerides were increased (? 1.695 mmol/L) in 31% and cholesterol (? 5.17 mmol/L) in 65%. Illiteracy (46%) was high and SES indicators generally low. Factors independently associated with DM2 included a diabetes family history (adjusted odds ratio (aOR), 3.8; 95% confidence interval (95%CI), 2.6-5.5), abdominal adiposity (aOR, 2.6; 95%CI, 1.8-3.9), increased triglycerides (aOR, 1.8; 95%CI, 1.1-3.0), and also several indicators of low SES. CONCLUSIONS: In this study from urban Ghana, DM2 affects predominantly obese patients of rather low socio-economic status and frequently is accompanied by hypertension and hyperlipidaemia. Prevention and management need to account for a specific risk profile in this population.

Project description:IntroductionWhilst the relationship between lipids and cardiovascular mortality has been well studied and appears to be controversial, very little has been explored in the context of rural-to-urban migration in low-resource settings.ObjectiveDetermine the profile and related factors for HDL-c patterns (isolated and non-isolated low HDL-c) in three population-based groups according to their migration status, and determine the effect of HDL-c patterns on the rates of cardiovascular outcomes (i.e. non-fatal stroke and non-fatal myocardial infarction) and mortality.MethodsCross-sectional and 5-year longitudinal data from the PERU MIGRANT study, designed to assess the effect of migration on cardiovascular risk profiles and mortality in Peru. Two different analyses were performed: first, we estimated prevalence and associated factors with isolated and non-isolated low HDL-c at baseline. Second, using longitudinal information, relative risk ratios (RRR) of composite outcomes of mortality, non-fatal stroke and non-fatal myocardial infarction were calculated according to HDL-c levels at baseline.ResultsData from 988 participants, rural (n = 201), rural-to-urban migrants (n = 589), and urban (n = 199) groups, was analysed. Low HDL-c was present in 56.5% (95%CI: 53.4%-59.6%) without differences by study groups. Isolated low HDL-c was found in 36.5% (95%CI: 33.5-39.5%), with differences between study groups. In multivariable analysis, urban group (vs. rural), female gender, overweight and obesity were independently associated with isolated low HDL-c. Only female gender, overweight and obesity were associated with non-isolated low HDL-c. Longitudinal analyses showed that non-isolated low HDL-c increased the risk of negative cardiovascular outcomes (RRR = 3.46; 95%CI: 1.23-9.74).ConclusionsIsolated low HDL-c was the most common dyslipidaemia in the study population and was more frequent in rural subjects. Non-isolated low HDL-c increased three-to fourfold the 5-year risk of cardiovascular outcomes.

Dataset Information

Addressing the impact of urban exposure on the incidence of type 2 diabetes mellitus: The PERU MIGRANT Study.

Publications

Addressing the impact of urban exposure on the incidence of type 2 diabetes mellitus: The PERU MIGRANT Study.

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