Sex differences in the association between diabetes and depressive symptoms: findings from Mexican National Health and Nutrition Survey 2018-2019.

AIMS: We set out to investigate the potential sex differences in the association between diabetes and depressive symptoms by conducting an interaction analysis, and to investigate whether sex mediates the effect of diabetes on depressive symptoms. METHODS: We conducted analyses on cross-sectional data of adults aged 20 years or older in the Mexican National Health and Nutrition Survey 2018-2019 (ENSANUT 2018-2019). Diabetes was defined by self-reported medical diagnosis, and depressive symptoms were measured using the seven-item Centre for Epidemiologic Studies Depression scale. First, an unadjusted interaction analysis was conducted. Second, the inverse probability of treatment weighting was applied to account for imbalances and biases. Third, the four-way decomposition method was used to estimate the potential mediating effect of sex. RESULTS: In the study population (N=43 074), the prevalence of diabetes was 9.3% for men and 11.7% for women. Depressive symptoms were more prevalent in women (19.0%) than in men (9.5%). Women with diabetes had the greatest odds of having depressive symptoms, compared with men without diabetes (ORwomen-diabetes3.49 (95% CI: 3.16 to 3.86)). The interaction analysis indicated that diabetes and sex interact on both, multiplicative and additive scales (ratio of ORs (95% CI) 1.22 (1.02 to 1.45), and relative excess risk due to interaction (95% CI) 0.99 (0.63 to 1.36)). The four-way decomposition analysis showed that the interaction effect between diabetes and sex is larger than the mediation effect. CONCLUSIONS: We found a positive interaction between diabetes and sex in the odds of having depressive symptoms. Mental health and diabetes care services planning would benefit from adopting a sex-informed approach.

Validity of Scottish predictors of child obesity (age 12) for risk screening in mid-childhood: a secondary analysis of prospective cohort study data-with sensitivity analyses for settings without various routinely collected predictor variables.

OBJECTIVE: To analyse the Growing Up in Scotland cohort for predictors of obesity at age 12, present at school entry (age 5-6). METHODS: The initial model included literature-based risk factors likely to be routinely collected in high-income countries (HICs), as well as "Adverse/Protective Childhood Experiences (ACEs/PCEs)". Missing data were handled by Multiple Chained Equations. Variable-reduction was performed using multivariable logistic regression with backwards and forwards stepwise elimination, followed by internal validation by bootstrapping. Optimal sensitivity/specificity cut-offs for the most parsimonious and accurate models in two situations (optimum available data, and routinely available data in Scotland) were examined for their referral burden, and Positive and Negative Predictive Values. RESULTS: Data for 2787 children with full outcome data (obesity prevalence 18.3% at age 12) were used to develop the models. The final "Optimum Data" model included six predictors of obesity: maternal body mass index, indoor smoking, equivalized income quintile, child's sex, child's BMI at age 5-6, and ACEs. After internal validation, the area under the receiver operating characteristic curve was 0.855 (95% CI 0.852-0.859). A cut-off based on Youden's J statistic for the Optimum Data model yielded a specificity of 77.6% and sensitivity of 76.3%. 37.0% of screened children were "Total Screen Positives" (and thus would constitute the "referral burden".) A "Scottish Data" model, without equivalized income quintile and ACEs as a predictor, and instead using Scottish Index of Multiple Deprivation quintile and "age at introduction of solid foods," was slightly less sensitive (76.2%) but slightly more specific (79.2%), leading to a smaller referral burden (30.8%). CONCLUSION: Universally collected, machine readable and linkable data at age 5-6 predict reasonably well children who will be obese by age 12. However, the Scottish treatment system is unable to cope with the resultant referral burden and other criteria for screening would have to be met.

Exploring the relationship between local food environments and obesity in UK, Ireland, Australia and New Zealand: a systematic review protocol.

INTRODUCTION: Obesity is a global pandemic that affects all socioeconomic strata, however, the highest figures have been observed in the most disadvantaged social groups. Evidence from the USA and Canada showed that specific urban settings encourage obesogenic behaviour in the population living and/or working there. We aim to examine the evidence on the association between local food environments and obesity in the UK, Ireland, Australia and New Zealand. METHODS: Six databases from 1990 to 2017 will be searched: MEDLINE (Ovid), Embase (Ovid), Scopus, The Cumulative Index to Nursing and Allied Health Literature (CINAHL), Applied Social Sciences Index and Abstracts (ASSIA) and Web of Science. Grey literature will also be sought by searching Opengrey Europe, The Grey Literature Report and relevant government websites. Additional studies will be retrieved from the reference lists of the selected articles. It will include cohort, longitudinal, case study and cross-sectional studies that have assessed the relationship between local food environments and obesity in the UK, Ireland, Australia and New Zealand regardless of sex, age and ethnicity of the population. Two researchers will independently select the studies and extract the data. Data items will incorporate: author names, title, study design, year of study, year exposure data collected, country, city, urban/rural, age range, study exclusions, special characteristics of study populations, aims, working definitions of food environments and food outlets, exposure and methods of data collection, outcomes and key findings. A narrative synthesis and a summary of the results will be produced separately for children and adults, according to the type of food exposure-outcome. All the selected studies will be assessed using The Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies. ETHICS AND DISSEMINATION: This study will be based on published literature, and therefore ethical approval has not been sought. Our findings will be presented at relevant national and international scientific conferences and published in a peer-reviewed journal.