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ObjectiveTo conduct a secondary data analysis detailing overweight prevalence and associations between key hypothesised determinants and overweight.DesignThis observational study used publicly available data from the Indonesian Family Life Survey (IFLS) (1993–2014). The IFLS is a home-based survey of adults and children that collected data on household characteristics (size, physical infrastructure, assets, food expenditures), as well as on individual-level educational attainment, occupation type, smoking status and marital status. These analyses used data on the self-reported consumption of ultra-processed foods and physical activity. Anthropometrics were measured.SettingIndonesia.Primary outcome measuresWe described the distribution of overweight by gender among adults (body mass index (BMI) ≥25 kg/m2) and by age among children, over time. Overweight was defined as weight-for-height z-score >2 among children aged 0–5 years and as BMI-for-age z-score >1 among children aged 6–18 years. We also described individuals who were overweight by selected characteristics over time. Finally, we employed multivariable logistic regression models to investigate risk factors in relation to overweight in 2014.ResultsOne-third of adults were overweight in 2014. Between 1993 and 2014, the prevalence of overweight among adults doubled from 17.1% to 33.0%. The prevalence of overweight among children under 5 years increased from 4.2% to 9.4% between 1993 and 2007, but then remained relatively stagnant between 2007 and 2014. Among children aged 6–12 years and 13–18 years, the prevalence of overweight increased from 5.1% to 15.6% and from 7.1% to 14.1% between 1993 and 2014, respectively. Although overweight prevalence remains higher in urban areas, the increase in overweight prevalence was larger among rural (vs urban) residents, and by 2014, the proportions of overweight adults were evenly distributed in each wealth quintile. Data suggest that the consumption of ultra-processed foods was common and levels of physical activity have decreased over the last decade. In multivariable models, urban area residence, higher wealth, higher education and consumption of ultra-processed foods were associated with higher odds of overweight among most adults and children.ConclusionUrgent programme and policy action is needed to reduce and prevent overweight among all ages.

Objective This longitudinal study aimed to measure precarious employment in the US using a multidimensional indicator. Methods We used data from the National Longitudinal Survey of Youth (1988-2016) and the Occupational Information Network database to create a longitudinal precarious employment score (PES) among 7568 employed individuals over 18 waves (N=101 290 observations). We identified 13 survey indicators to operationalize 7 dimensions of precarious employment, which we included in our PES (range: 0-7, with 7 indicating the most precarious): material rewards, working-time arrangements, stability, workers' rights, collective organization, interpersonal relations, and training. Using generalized estimating equations, we estimated the mean PES and changes over time in the PES overall and by race/ethnicity, gender, education, income, and region. Results On average, the PES was 3.17 [standard deviation (SD) 1.19], and was higher among women (3.34, SD 1.20), people of color (Hispanics: 3.24, SD 1.23; non-Hispanic Blacks: 3.31, SD 1.23), those with less education (primary: 3.99, SD 1.07; high school: 3.43, SD 1.19), and with lower-incomes (3.84, SD 1.08), and those residing in the South (3.23, SD 1.17). From 1988 to 2016, the PES increased by 9% on average [0.29 points; 95% confidence interval (CI) 0.26-0.31]. While precarious employment increased over time across all subgroups, the increase was largest among males (0.35 points; 95% CI 0.33-0.39), higher-income (0.39 points; 95% CI 0.36-0.42) and college-educated (0.37 points; 95% CI 0.33-0.41) individuals. Conclusions Long-term decreases in employment quality are widespread in the US. Women and those from racialized and less-educated populations remain disproportionately precariously employed; however, we observed the largest increases among men, college graduates and higher-income individuals.

El Niño Southern Oscillation (ENSO) has been shown to relate to the epidemiology of childhood infectious diseases, but evidence for whether they increase child deaths is limited. Here, we investigate the impact of mothers’ ENSO exposure during and prior to delivery on child mortality by constructing a retrospective cohort study in 38 low- and middle-income countries. We find that high levels of ENSO indices cumulated over 0–12 lagged months before delivery are associated with significant increases in risks of under-five mortality; with the hazard ratio ranging from 1.33 (95% confidence interval [CI], 1.26, 1.40) to 1.89 (95% CI, 1.78, 2.00). Child mortality risks are particularly related to maternal exposure to El Niño-like conditions in the 0th–1st and 6th–12th lagged months. The El Niño effects are larger in rural populations and those with unsafe sources of drinking water and less education. Thus, preventive interventions are particularly warranted for the socio-economically disadvantaged. El Niño Southern Oscillation (ENSO) has been shown to relate to the epidemiology of child infectious diseases, but evidence for child deaths is limited. Here, the authors show that maternal exposure to high levels of ENSO before conception and giving birth may increase under-five mortality.

Lung cancer incidence and mortality rates are higher in Non-Hispanic Black (NHB) compared to Non-Hispanic White (NHW) individuals in the Chicago metropolitan area, which may be related to exposure to chronic stress which may increase inflammation. We investigated disparities in inflammation as measured by neutrophil to lymphocyte ratio (NLR) in individuals with lung cancer by race and by neighborhood concentrated disadvantage index (CDI). This retrospective, cross-sectional study included 263 NHB and NHW adults with lung cancer. We analyzed NLR as a continuous and categorical variable to determine degree and prevalence of inflammation. We used Mann Whitney U, t-tests, Chi square tests, linear and logistic regression models as appropriate. More than 60% of subjects had inflammation (NLR ≥ 3) at lung cancer diagnosis. The degree of inflammation was significantly lower in NHB (NLR 5.50 +/- 7.45) compared to NHW individuals (NLR 6.53 +/- 6.53; p=0.01) but did not differ by neighborhood CDI. The prevalence of inflammation (NLR ≥ 3) was significantly lower in NHB (55.07%) compared to NHW individuals (71.20%; p<0.01) and in those from the most disadvantaged (54.07%) compared to the least disadvantaged (71.88%; p<0.01) neighborhoods. At lung cancer diagnosis, there is a lower degree and prevalence of inflammation in NHB compared to NHW individuals, and lower prevalence in those residing in the most disadvantaged neighborhoods. Further research is needed to determine mechanisms of inflammation that may be contributing to lung cancer disparities as well as whether NLR is an appropriate biomarker when examining racial differences in inflammation.

Several studies have suggested that record high unemployment during the Great Recession was associated with deleterious changes in diet and weight-related health. However, studies have yet to explore whether the Great Recession was also associated with obesity-related health in utero. We investigated whether increasing county-level unemployment was associated with large-for-gestational age (LGA) births, using repeated cross-sectional data from California birth records between 2008 and 2011 (n = 1,715,052). LGA was defined as >90th percentile, using the Oken reference. We use the annual 1-year lagged value for county-level unemployment (2007-2010) and limit our analyses to singleton, term births. Linear probability models, with county and year fixed-effects were used to examine the unemployment-LGA association. All models control for county-level foreclosure rates, child gender, and maternal age, parity, education, and race/ethnicity. An increase in county-level unemployment was not statistically significantly associated with the prevalence of LGA (percentage point [PP]: 0.12; 95% CI: -0.02, 0.25). But, over the period of observation, for every one standard deviation increase in unemployment, LGA prevalence increased by 5% and p = 0.08. These results cautiously suggest some deleterious effects of the Great Recession on obesity-related health in utero.

To conduct a secondary data analysis detailing the associations between sociodemographic and behavioral factors and nutrition-related chronic disease. These analyses utilized 2014 data from the Indonesian Family Life Survey, a home-based survey that collected socioeconomic, dietary intake, physical activity, and biological data among adults. We explored four outcomes in relation to sociodemographic and behavioral determinants: 1) hypertension, 2) elevated high-sensitivity c-reactive protein (hs-CRP), and 3) central obesity, as these are critical metabolic determinants in the progression to cardiovascular disease, and 4) type 2 diabetes. Hypertension was defined as systolic blood pressure ≥140 mm or diastolic blood pressure ≥ 90mm or current use of antihypertensive medication. Elevated hs-CRP was defined as hs-CRP >3 mg/dL. Central obesity was defined as waist circumference ≥ 90 cm if male and waist circumference ≥ 80 cm if female, which are specific to South Asia. Type 2 diabetes was defined as glycated hemoglobin ≥ 6.5%. We employed separate gender-stratified multivariate logistic regression models to test the associations between sociodemographic and behavioral determinants and each nutrition-related chronic disease outcome. All analyses employed sampling weights, which account for the survey design. In 2014, about 30% of adults were hypertensive and one-fifth had elevated hs-CRP. Approximately 70% of women had central obesity and 11.6% of women and 8.9% of men had diabetes. Older-age was consistently associated with nutrition-related chronic disease and being overweight was associated with hypertension, elevated hs-CRP, and type 2 diabetes. Regularly consuming instant noodles (women) and soda (men) were associated with elevated hs-CRP and soda consumption was associated with central obesity among men. Large segments of the adult population in Indonesia now have or are at risk for non-communicable disease. Our analyses provide preliminary empirical evidence that interventions that target healthful food intake (e.g. reduce the intake of ultra-processed foods) should be considered and that the reduction of overweight is critical for preventing chronic diseases in Indonesia.

Background In 2024, approximately 84,100 adolescents and young adults (AYAs) between 15 and 39 years old received a cancer diagnosis. Aims Given their unique psychosocial, economic, and clinical stressors, we examined whether AYA cancer patients living in deprived neighborhoods have a higher risk of suicide when compared to those in the least deprived neighborhoods. Materials & Methods Our sample comprised 486,374 AYA cancer patients from the Surveillance, Epidemiology, and End Results (SEER) dataset between 2006 and 2020. We use Cox proportional hazard models to test the relation between quintiles of neighborhood deprivation, from Q1 (most deprived) to Q5 (least deprived), and survival months until suicide mortality from the time of cancer diagnosis. Results We find that AYA cancer patients living in more deprived neighborhoods (Q1, Q2, Q4) have a higher risk of suicide when compared to those in the least deprived neighborhoods (Q5) (Q1: HR—1.82 [1.14–2.90]; Q2: HR—1.95 [1.35–2.81]; Q4: HR—1.48 [1.05–2.07]). Discussion Mental health services and monitoring from treatment through survivorship may support suicide prevention efforts for young cancer patients. Conclusion Early identification of high‐risk AYA cancer patients living in deprived areas may help target suicide prevention interventions.

Background High neighborhood deprivation is linked to increased cancer and overall mortality. Prior studies demonstrated higher inflammation in people from high deprivation areas. The area deprivation index (ADI) is a composite measure of income, education, employment, and housing, which quantifies neighborhood deprivation. We used the All of Us dataset to test whether inflammation, measured via c‐reactive protein (CRP), albumin, and the neutrophil‐to‐lymphocyte ratio (NLR), differs by ADI in cancer survivors. Methods Our sample included individuals with a history of lung, breast, prostate, and colorectal cancer, filtered for the presence of the inflammatory biomarkers. We used quartiles of ADI based on 3‐digit zip code and biomarkers from electronic health records. We estimated the association between ADI and inflammation using adjusted logistic regression (n = 690 for CRP; n = 4242 for albumin; n = 5183 for NLR). Results The sample had a mean age of 66.2 ± 10.1 years, 63.0% were female, and 86.8% were White. Mean CRP (11.5 ± 17.5 mg/L) and NLR (3.6 ± 2.2) indicated moderate to high inflammation. In the fully adjusted model, there were 2.04 (95% CI:1.02, 4.11) and 2.17 higher odds (95% CI:1.16, 4.13) of elevated CRP when comparing quartile 4 and quartile 3, respectively, to the lowest ADI quartile. Regression models were not significant for albumin or NLR. Conclusion Area deprivation is associated with CRP, a marker of stress that may lead to a higher risk of chronic diseases among cancer survivors. Future studies using a sample of cancer survivors with a wider range of ADI may help to strengthen this association.

To describe the food environments experienced by American Indians living on tribal lands in California. Geocoded statewide food business data were used to define and categorize existing food vendors into healthy, unhealthy, and intermediate composite categories. Distance to and density of each of the composite food vendor categories for tribal lands and nontribal lands were compared using multivariate linear regression. Quantitative results were concurrently triangulated with qualitative data from in-depth interviews with tribal members (n = 24). After adjusting for census tract-level urbanicity and per capita income, results indicate there were significantly fewer healthy food outlets per square mile for tribal areas compared to non-tribal areas. Density of unhealthy outlets was not significantly different for tribal versus non-tribal areas. Tribal members perceived their food environment negatively and reported barriers to the acquisition of healthy food. Urbanicity and per capita income do not completely account for disparities in food environments among American Indians tribal lands compared to nontribal lands. This disparity in access to healthy food may present a barrier to acting on the intention to consume healthy food.