Sweetened beverages, snacks and overweight: findings from the Young Lives cohort study in Peru

OBJECTIVE: To determine the association between consumption of snacks and sweetened beverages and risk of overweight among children. DESIGN: Secondary analysis of the Young Lives cohort study in Peru. SETTING: Twenty sentinel sites from a total of 1818 districts available in Peru. SUBJECTS: Children in the younger cohort of the Young Lives study in Peru, specifically those included in the third (2009) and the fourth (2013) rounds. RESULTS: A total of 1813 children were evaluated at baseline; 49·2 % girls and mean age 8·0 (sd 0·3) years. At baseline, 3·3 (95 % CI 2·5, 4·2) % reported daily sweetened beverage consumption, while this proportion was 3·9 (95 % CI 3·1, 4·9) % for snacks. Baseline prevalence of overweight was 22·0 (95 % CI 20·1, 23·9) %. Only 1414 children were followed for 4·0 (sd 0·1) years, with an overweight incidence of 3·6 (95 % CI 3·1, 4·1) per 100 person-years. In multivariable analysis, children who consumed sweetened beverages and snacks daily had an average weight increase of 2·29 (95 % CI 0·62, 3·96) and 2·04 (95 % CI 0·48, 3·60) kg more, respectively, than those who never consumed these products, in approximately 4 years of follow-up. Moreover, there was evidence of an association between daily consumption of sweetened beverages and risk of overweight (relative risk=2·12; 95 % CI 1·05, 4·28). CONCLUSIONS: Daily consumption of sweetened beverages and snacks was associated with increased weight gain v. never consuming these products; and in the case of sweetened beverages, with higher risk of developing overweight

Stroke-related length of hospitalization trends and in-hospital mortality in Peru

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 = <0.001). The case fatality rate (CFR) of patients with stroke was 11.5% (95% CI [10-12%]). Subarachnoid hemorrhage (HR = 2.45; 95% CI [1.91-3.14]), intracerebral hemorrhage (HR = 1.95; 95% CI [1.55-2.46]), and stroke not specified as hemorrhage or infarction (HR = 1.45; 95% CI [1.16-1.81]) were associated with higher in-hospital mortality risk in comparison to ischemic strokes. DISCUSSION: Between 2002 and 2017, LOS due to stroke has not changed in Peru in stroke patients discharged alive. Hemorrhagic cases had the longest LOS and highest in-hospital mortality risk during 2016 and 2017. The findings of our study seem to be consistent with a previous study carried out in Peru and similar to that of HIC and LMIC, also there is an increased median LOS in stroke cases managed in specialized centers. Likewise, LOS seems to depend on the type of stroke, where ischemic stroke cases have the lowest LOS. Peru needs to improve access to stroke care

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

Valid group comparisons can be made with the Patient Health Questionnaire (PHQ-9): A measurement invariance study across groups by demographic characteristics

This is the final version. Available on open access from Public Library of Science via the DOI in this recordData Availability: The database is freely accessible from the website of the National Institute of Statistics of Peru, URL: http://iinei.inei.gob.pe/microdatos/ The information can be obtained by entering the survey query tab and selecting the ENDES data using the health module data. Only cross-sectional information from 2016 ENDES Health Questionnaire was used.Objective Analyze the measurement invariance and the factor structure of the Patient Health Questionnaire-9 (PHQ-9) in the Peruvian population. Method Secondary data analysis performed using cross-sectional data from the Health Questionnaire of the Demographic and Health Survey in Peru. Variables of interest were the PHQ-9 and demographic characteristics (sex, age group, level of education, socioeconomic status, marital status, and area of residence). Factor structure was evaluated by standard confirmatory factor analysis (CFA), and measurement invariance by multi-group CFA, using standard goodness-of-fit indices criteria for interpreting results from both CFAs. Analysis of the internal consistency (α and ω) was also pursued. Results Data from 30,449 study participants were analyzed, 56.7% were women, average age was 40.5 years (standard deviation (SD) = 16.3), 65.9% lived in urban areas, 74.6% were married, and had 9 years of education on average (SD = 4.6). From standard CFA, a one-dimensional model presented the best fit (CFI = 0.936; RMSEA = 0.089; SRMR = 0.039). From multi-group CFA, all progressively restricted models had ΔCFI<0.01 across almost all groups by demographic characteristics. PHQ-9 reliability was optimal (α = ω = 0.87). Conclusions The evidence presents support for the one-dimensional model and measurement invariance of the PHQ-9 measure, allowing for reliable comparisons between sex, age groups, education level, socioeconomic status, marital status, and residence area, and recommends its use within the Peruvian population.Universidad Católica los Ángeles de Chimbote (ULADECH-Católica)PSYCOPERU Peruvian Research Institute of Educational and Social Psycholog

Analysis of dietary patterns and cross-sectional and longitudinal associations with hypertension, high BMI and type 2 diabetes in Peru

OBJECTIVE: To determine if specific dietary patterns are associated with risk of hypertension, type 2 diabetes mellitus (T2DM) and high BMI in four sites in Peru. DESIGN: We analysed dietary patterns from a cohort of Peruvian adults in four geographical settings using latent class analysis. Associations with prevalence and incidence of hypertension, T2DM and high BMI were assessed using Poisson regression and generalised linear models, adjusted for potential confounders. SETTING: Four sites in Peru varying in degree of urbanisation. PARTICIPANTS: Adults aged ≥35 years (n 3280). RESULTS: We identified four distinct dietary patterns corresponding to different stages of the Peruvian nutrition transition, reflected by the foods frequently consumed in each pattern. Participants consuming the 'stage 3' diet, characterised by high proportional consumption of processed foods, animal products and low consumption of vegetables, mostly consumed in the semi-urban setting, showed the highest prevalence of all health outcomes (hypertension 32·1 %; T2DM 10·7 %; high BMI 75·1 %). Those with a more traditional 'stage 1' diet characterised by potato and vegetables, mostly consumed in the rural setting, had lower prevalence of hypertension (prevalence ratio; 95 CI: 0·57; 0·43, 0·75), T2DM (0·36; 0·16, 0·86) and high BMI (0·55; 0·48, 0·63) compared with the 'stage 3' diet. Incidence of hypertension was highest among individuals consuming the 'stage 3' diet (63·75 per 1000 person-years; 95 % CI 52·40, 77·55). CONCLUSIONS: The study found more traditional diets were associated with a lower prevalence of three common chronic diseases, while prevalence of these diseases was higher with a diet high in processed foods and low in vegetables

Glycated haemoglobin (HbA1c ) and fasting plasma glucose relationships in sea-level and high-altitude settings.

AIM: Higher haemoglobin levels and differences in glucose metabolism have been reported among high-altitude residents, which may influence the diagnostic performance of HbA1c . This study explores the relationship between HbA1c and fasting plasma glucose (FPG) in populations living at sea level and at an altitude of > 3000 m. METHODS: Data from 3613 Peruvian adults without a known diagnosis of diabetes from sea-level and high-altitude settings were evaluated. Linear, quadratic and cubic regression models were performed adjusting for potential confounders. Receiver operating characteristic (ROC) curves were constructed and concordance between HbA1c and FPG was assessed using a Kappa index. RESULTS: At sea level and high altitude, means were 13.5 and 16.7 g/dl (P > 0.05) for haemoglobin level; 41 and 40 mmol/mol (5.9% and 5.8%; P < 0.01) for HbA1c ; and 5.8 and 5.1 mmol/l (105 and 91.3 mg/dl; P < 0.001) for FPG, respectively. The adjusted relationship between HbA1c and FPG was quadratic at sea level and linear at high altitude. Adjusted models showed that, to predict an HbA1c value of 48 mmol/mol (6.5%), the corresponding mean FPG values at sea level and high altitude were 6.6 and 14.8 mmol/l (120 and 266 mg/dl), respectively. An HbA1c cut-off of 48 mmol/mol (6.5%) had a sensitivity for high FPG of 87.3% (95% confidence interval (95% CI) 76.5 to 94.4) at sea level and 40.9% (95% CI 20.7 to 63.6) at high altitude. CONCLUSION: The relationship between HbA1c and FPG is less clear at high altitude than at sea level. Caution is warranted when using HbA1c to diagnose diabetes mellitus in this setting

Obesity risk in rural, urban and rural-to-urban migrants: prospective results of the PERU MIGRANT study.

BACKGROUND: Although 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. METHODS: Prospective 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. RESULTS: At 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). CONCLUSIONS: Peruvian 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

Association between television viewing and obesity in Peruvian women

OBJECTIVE: To assess the association between frequency of television viewing, overweight and obesity in a nationally representative sample of Peruvian women. METHODS: Secondary analysis of the Demographic and Health Survey 2008 including women aged from 15 to 49 years old. The outcome variables were obesity (body mass index &gt;30 kg/m²) and overweight (body mass index &gt;25 butOBJETIVO: Evaluar la asociación entre frecuencia de ver televisión, sobrepeso y obesidad en una muestra representativa de mujeres peruanas a nivel nacional. MÉTODOS: Análisis secundario de la Encuesta Nacional Demográfica y de Salud Familiar incluyendo mujeres de 15 a 49 años. Las variables resultados fueron obesidad (índice de masa corporal &gt;30 kg/m²) y sobrepeso (&gt;25 pesoOBJETIVO: Analisar a associação entre frequência de assistir televisão com sobrepeso e obesidade em uma amostra representativa de mulheres peruanas em nível nacional. MÉTODOS: Análise secundária da Pesquisa Nacional Demográfica e de Saúde Familiar incluindo 27.712 mulheres de 15 a 49 anos em 2008. As variáveis-desfecho foram obesidade (índice de massa corporal >; 30 kg/m2) e sobrepeso (entre 25 e 30 kg/m2); a variável de exposição foi a frequência de assistir televisão (nunca, ocasionalmente, quase todos os dias). Foi utilizada regressão logística para amostras complexas, ajustada por potenciais confundidores. Os resultados foram apresentados como odds ratios ajustados (ORa) com seus respectivos intervalos de 95% de confiança. RESULTADOS: A prevalência de sobrepeso foi de 34,7% (IC95% 33,8;35,7) e de obesidade, 14,3% (IC95% 13,6;5,1). Mulheres que assistiam televisão ocasionalmente e quase todos os dias tiveram maior probabilidade de ter obesidade em comparação às que não assistiam: ORa = 1,7 (IC95% 1,3;2,3) e ORa 2,6 (IC95% 2,0;3,5), respectivamente. A magnitude da associação foi menor para o sobrepeso: ORa 1,2 (IC95% 1,3;2,3) e ORa 1,6 (IC95% 1,1;1,4), respectivamente. A associação foi mais forte na área urbana. CONCLUSÕES: A frequência de assistir televisão esteve associada à apresentar obesidade e sobrepeso entre mulheres peruanas, e a força da associação variou de acordo com a área de residência. Estes achados podem auxiliar estratégias de prevenção da obesidade no contexto peruano

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