The associations of body mass index (BMI) and other anthropometric measurements with lung cancer were examined in 348,108 participants in the European Investigation Into Cancer and Nutrition (EPIC) between 1992 and 2010. The study population included 2,400 case patients with incident lung cancer, and the average length of follow-up was 11 years. Hazard ratios were calculated using Cox proportional hazard models in which we modeled smoking variables with cubic splines. Overall, there was a significant inverse association between BMI (weight (kg)/height (m)(2)) and the risk of lung cancer after adjustment for smoking and other confounders (for BMI of 30.0-34.9 versus 18.5-25.0, hazard ratio = 0.72, 95% confidence interval: 0.62, 0.84). The strength of the association declined with increasing follow-up time. Conversely, after adjustment for BMI, waist circumference and waist-to-height ratio were significantly positively associated with lung cancer risk (for the highest category of waist circumference vs. the lowest, hazard ratio = 1.25, 95% confidence interval: 1.05, 1.50). Given the decline of the inverse association between BMI and lung cancer over time, the association is likely at least partly due to weight loss resulting from preclinical lung cancer that was present at baseline. Residual confounding by smoking could also have influenced our findings.

Food fortification programs have been conducted in several countries to overcome micronutrient deficiency and related problems with various degrees of effectiveness. Available information regarding the success of food fortification programs in some developing countries, including Indonesia, is still limited. Thus, this study conducts a systematic review of the effects of food fortification of mothers and children using biochemical and anthropometric measures focusing on linear growth. Three databases were used in the literature search, namely PubMed, Science Direct and Google Scholar. Fifteen articles were included for analysis from 517 studies found consisting of Indonesian and English articles published from 2000 to June 2020. Fortification of iron, vitamin A, and iodine can increase the level of hemoglobin, serum ferritin, and serum retinol and median urine iodine excretion, especially in toddlers and schoolchildren. However, multinutrient fortification interventions were associated with various effects on hemoglobin, serum ferritin, and serum retinol but a positive association was found with linear growth indicators in the form of body length for age. The effectiveness of food fortification in reducing the prevalence of stunting still needs more and stronger evidence through studies with large sample size and longer duration.

BACKGROUND: The increased risk of malnutrition is affected by food insecurity. Studies in adolescents still show mixed results.  AIM: This article aimed to evaluate the association between food insecurity and anthropometry measurements in studies involving adolescents.  MATERIALS AND METHODS: The databases used to obtain the literature were PubMed, ScienceDirect, MEDLINE, and PubMed Central. The keywords used were food security, food insecurity, hunger, malnutrition, obesity, adolescence, adolescents, teenagers, teens, and youth in studies published from 2010 to 2019. A total of 12 articles were used in this review.  RESULTS: The association between food insecurity and the incidence of malnutrition in adolescents in various regions is still diverse. Food insecurity had a negative correlation with BMI-for-age in three studies (33.3%), but one study (11.1%) showed the opposite result. Food insecurity was positively related to low height-for-age (stunting) in 50% of studies, while five other studies (55.6%) showed that food insecurity was not related to BMI-for-age or weight-for-age. Three studies (50%) showed that there was no association between food insecurity and height-for-age.  CONCLUSION: Longitudinal studies, such as Cohort studies, need to be conducted to ensure the actual relationship between food insecurity and nutritional status in various regions.

The prevalence of overweight and obesity in adult groups in Indonesia experience a surge compared to the previous year. The obesity determinants are classified as complex, and they can differ between regions. Appropriate policies, in accordance with determinants, play an important role in efforts to reduce the prevalence of obesity. This study aimed to identify the determinant factors for overweight and obesity in Indonesia and policies that supported a decrease in the prevalence of overweight and obesity based on the significant determinant factors found. The data sources were from the Ministry of Health, Statistics Indonesia, and the Ministry of Agriculture for 33 provinces in Indonesia. The literature regarding policy analysis was sought on Google, the IPB University repositories, related ministry websites, PubMed, ScienceDirect, and MEDLINE. The multiple regression analysis was performed to identify the determinants of overweight and obesity while the Five-E approach was used to analyze related policies. The simple regression analysis showed that the consumption of animal source foods (p=0.001), oil and fat consumption (p=0.006), the proportion of the population with low physical activity (p=0.01), the average study duration (p=0.001), total per capita expenditure (p=0.000), food (p=0.001) and non-food expenditure (p=0.000), and share of food expenditure (p=0.005) had significant effects on the proportion of adulthood overweight and obesity. Only oil and fat consumption (p=0.02) still had a significant positive effect on the proportion of overweight and obesity after performing the multiple regression analysis. Vegetable consumption (p=0.03) also had a significant negative effect on the proportion of overweight and obesity after being included in the multiple regression model. The Healthy Community Movement (HMC or known as GERMAS in Indonesia) policy and the inclusion of fat content into food labels are policies for preventing and managing overweight, which are conducted related to consumption of vegetables, fat, and oil. The effectiveness of the policy is still not optimal even though the policy is efficient. An improvement of the policy implementation needs to be conducted by optimizing the implementation of follow-up monitoring and evaluation of the implementation of program policies.

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