Ageing, one of the largest risk factors for many complex diseases, is highly interconnected to metabolic processes. Investigating the changes in metabolite concentration during ageing among healthy individuals offers us unique insights to healthy ageing. We aim to identify ageing-associated metabolites that are independent from chronological age to deepen our understanding of the long-term changes in metabolites upon ageing. Sex-stratified longitudinal analyses were performed using fasting serum samples of 590 healthy KORA individuals (317 women and 273 men) who participated in both baseline (KORA S4) and seven-year follow-up (KORA F4) studies. Replication was conducted using serum samples of 386 healthy CARLA participants (195 women and 191 men) in both baseline (CARLA-0) and four-year follow-up (CARLA-1) studies. Generalized estimation equation models were performed on each metabolite to identify ageing-associated metabolites after adjusting for baseline chronological age, body mass index, physical activity, smoking status, alcohol intake and systolic blood pressure. Literature researches were conducted to understand their biochemical relevance. Out of 122 metabolites analysed, we identified and replicated five (C18, arginine, ornithine, serine and tyrosine) and four (arginine, ornithine, PC aa C36:3 and PC ae C40:5) significant metabolites in women and men respectively. Arginine decreased, while ornithine increased in both sexes. These metabolites are involved in several ageing processes: apoptosis, mitochondrial dysfunction, inflammation, lipid metabolism, autophagy and oxidative stress resistance. The study reveals several significant ageing-associated metabolite changes with two-time-point measurements on healthy individuals. Larger studies are required to confirm our findings.

The growing burden of non-communicable diseases (NCDs) and an increase in the prevalence of the underlying risk factors are creating a challenge to health systems in low- and middle-income countries (LMICs). In Nepal, deaths attributable to NCDs have been increasing, as has life expectancy. This poses questions with regards to how age and various risk factors interact in affecting NCDs. We analyzed the effects of age on NCD risk factors, using data from the Nepalese STEPs survey 2019, a nationally representative cross-sectional study. Six sociodemographic determinants, four behavioral risk factors, and four biological risk factors were examined. Age effects were analyzed among three age groups: below 35 years (young), 35–59 years (middle aged) and 60 years and above (elderly). The prevalence of selected behavioral risk factors for NCDs, notably smoking, alcohol consumption and insufficient physical activity, and some biological risk factors (hypertension, hyperlipidemia) increases with age. The prevalence of most behavioral risk factors was highest among men and women aged 60 years and above. The prevalence of hypertension and hyperlipidemia was highest among the elderly, but the prevalence of diabetes and overweight/obesity was highest among the middle aged for both sexes. Age interactions in the association between behaviors and biological risk factors were surprisingly weak. However, age interactions were significant in the association between alcohol consumption and -hypertension, -overweight/obesity and -hyperlipidemia among women. While the prevalence of NCD risk factors tends to be higher among elders, the interaction between age and risk factors is complex. Most NCD risk factors are related to behaviors, which originate in young adulthood. It is necessary to diagnose and treat biological risk factors, in younger age groups before they manifest as NCDs. Similarly, behavior change interventions need to target these younger age groups to reduce the risk of NCDs later in life.

Indonesia has limited data on asbestos-related diseases despite abundant use. This study investigated the risk of occupational asbestos exposure for lung cancer development, utilizing a hospital-based case-control study. Subjects were patients who received a thoracic CT scan at Persahabatan Hospital, Jakarta. The cases had primary lung cancer confirmed by histology, the controls were negative for lung cancer. The cumulative occupational asbestos exposure was calculated by multiplying the exposure intensity by the years of exposure. The exposure intensity was obtained by adopting the weighted arithmetic mean value of asbestos exposure from a job-exposure matrix developed in Korea. The primary data analysis was based on logistic regression. The study included 696 subjects, with 336 cases and 360 controls. The chance of lung cancer for subjects exposed to asbestos was doubled (OR = 2.04, 95% CI = 1.21–3.42) compared with unexposed, and subjects with a cumulative asbestos exposure of 10 fiber-years or more even showed an OR of 3.08 (95% CI = 1.01–9.46). The OR of the combined effect between smoking and asbestos was 8.7 (95% CI = 1.71–44.39); the interaction was consistent with an additive and multiplicative risk model. Asbestos exposure is associated with a higher chance of lung cancer. Improved policies are needed to protect the population from asbestos hazards.

In a town located in a desert area of Northern Chile, gold and copper open-pit mining is carried out involving explosive processes. These processes are associated with increased dust exposure, which might affect children’s respiratory health. Therefore, we aimed to quantify the causal attributable risk of living close to the mines on asthma or allergic rhinoconjunctivitis risk burden in children. Data on the prevalence of respiratory diseases and potential confounders were available from a cross-sectional survey carried out in 2009 among 288 (response: $69\%$ ) children living in the community. The proximity of the children’s home addresses to the local gold and copper mine was calculated using geographical positioning systems. We applied targeted maximum likelihood estimation to obtain the causal attributable risk (CAR) for asthma, rhinoconjunctivitis and both outcomes combined. Children living more than the first quartile away from the mines were used as the unexposed group. Based on the estimated CAR, a hypothetical intervention in which all children lived at least one quartile away from the copper mine would decrease the risk of rhinoconjunctivitis by $4.7$ percentage points (CAR: $-4.7$ ; $95\%$ confidence interval ( $95\%$ CI): $-8.4$ ; $-0.11$ ); and $4.2$ percentage points (CAR: $-4.2$ ; $95\%$ CI: $-7.9$ ; $-0.05$ ) for both outcomes combined. Overall, our results suggest that a hypothetical intervention intended to increase the distance between the place of residence of the highest exposed children would reduce the prevalence of respiratory disease in the community by around four percentage points. This approach could help local policymakers in the development of efficient public health strategies.

In Indonesia, many occupations and industries involve a variety of hazardous and toxic materials. The ILO estimates that about 21.1% of the tracheal, bronchial, and lung cancer deaths among men were attributable to workplace hazardous substances. This study investigated the relationship between occupations or workplace exposure and the risk of lung cancer in the country. The results will help determine how Indonesia can best mitigate the risk for its workers. This case-control study utilizes the Indonesian Standard of Industrial Classification (IndSIC) 2015 with the aim of exploring the risk of lung cancer among Indonesian workers. The study included patients aged 35 years old or older receiving thoracic CT at the radiology department of Persahabatan Hospital. The cases were histological-confirmed primary lung cancers, while the controls were negative thoracic CT scan for lung cancer. The subjects’ job titles and industries were classified according to IndSIC 2015 and blind to the patient’s grouping as a case or control. Logistic regression was used to determine the odds ratios for lung cancer among all sections and some divisions or groups of IndSIC 2015. The mean age was 58.1 (±10.23) years for lung cancer patients and 54.5 (±10.23) years for controls. The majority of subjects (19.6%) worked in Section G (Wholesale and retail trade; repair of motor vehicles and motorcycle). After adjusting for age, gender, level of education, and smoking habit, the risk of lung cancer was nearly three-times higher (OR = 2.8, 95% CI = 1.11–7.02) in workers of Division A01 (crop, animal production, and hunting) and two-times higher (OR = 1.9, 95% CI = 1.05–3.46) in workers of Section F (construction) compared to the workers in other sections or divisions. The excess risk of lung cancer among certain categories of workers confirms the need for improved policy, monitoring, and control of occupational exposure for primary cancer prevention and workers’ compensation purposes.