Little information is available on the association between gender nonconformity during adolescence and subsequent mental health. While the distress related to gender nonconformity may be socially produced rather than attributed to individual-level factors, further research is needed to better understand the role of psychosocial factors in this context.

We analyzed data from the Tokyo Teen Cohort, obtained through random sampling of adolescents born between 2002 and 2004. We used inverse probability weighting to examine the association of gender nonconformity at ages 12 and 14 as a time-varying variable with subsequent mental health at age 16, while accounting for time-fixed and time-varying confounders. Furthermore, we used a weighting approach to investigate the mediating role of modifiable psychosocial factors in this association, addressing exposure-mediator and mediator–mediator interactions.

A total of 3171 participants were analyzed. Persistent gender nonconforming behavior at ages 12 and 14 was associated with subsequent depression (β = 2.02, 95% confidence interval [CI] 0.85 to 3.19) and psychotic experiences (β = 0.33, 95% CI 0.14 to 0.52) at age 16. The results remained robust in sensitivity analyses. Approximately 30% of the association between gender nonconformity and depression was consistently mediated by a set of psychosocial factors, namely loneliness, bullying victimization, and relationships with mother, father, and friends.

Persistent gender nonconformity during adolescence is associated with subsequent mental health. Psychosocial factors play a vital mediating role in this association, highlighting the essential need for social intervention and change to reduce stigmatization and ameliorate mental health challenges.

To examine whether using grocery delivery services moderates the relationship between distance to supermarket and dietary variety among Japanese older adults.

We conducted a 1-year prospective cohort study. Distance to supermarket was measured using geographic information systems. We collected information on dietary variety score (range 0–10), regular use of grocery delivery services and socio-demographic factors using a questionnaire delivered via post.

The current study was performed in Nada Ward, Kobe City, Japan, from 2017 to 2018.

Older adults living in Nada Ward (n 778).

The linear mixed model showed that a longer distance to supermarket (per 100 m: B = –0·07, 95 % CI –0·14, –0·01, P = 0·048) significantly predicted lower dietary variety after adjusting for socio-demographic factors. Using grocery delivery services (B = 0·28, 95 % CI –0·08, 0·64, P = 0·127) did not significantly predict dietary variety, and neither did its interaction with distance to supermarket (B = –0·04, 95 % CI –0·17, 0·10, P = 0·604).

The current study found that longer distance to supermarket was associated with lower dietary variety among Japanese older adults and that the use of grocery delivery services did not moderate this association. The findings imply that the use of grocery delivery services is insufficient to reduce the negative influence of inconvenient food access on dietary variety among older adults.

Indirect comparisons via a common comparator (anchored comparisons) are commonly used in health technology assessment. However, common comparators may not be available, or the comparison may be biased due to differences in effect modifiers between the included studies. Recently proposed population adjustment methods aim to adjust for differences between study populations in the situation where individual patient data are available from at least one study, but not all studies. They can also be used when there is no common comparator or for single-arm studies (unanchored comparisons). We aim to characterise the use of population adjustment methods in technology appraisals (TAs) submitted to the United Kingdom National Institute for Health and Care Excellence (NICE).

We reviewed NICE TAs published between 01/01/2010 and 20/04/2018.

Population adjustment methods were used in 7 percent (18/268) of TAs. Most applications used unanchored comparisons (89 percent, 16/18), and were in oncology (83 percent, 15/18). Methods used included matching-adjusted indirect comparisons (89 percent, 16/18) and simulated treatment comparisons (17 percent, 3/18). Covariates were included based on: availability, expert opinion, effective sample size, statistical significance, or cross-validation. Larger treatment networks were commonplace (56 percent, 10/18), but current methods cannot account for this. Appraisal committees received results of population-adjusted analyses with caution and typically looked for greater cost effectiveness to minimise decision risk.

Population adjustment methods are becoming increasingly common in NICE TAs, although their impact on decisions has been limited to date. Further research is needed to improve upon current methods, and to investigate their properties in simulation studies.