Sex/gender and socioeconomic differences in modifiable risk factors for dementia

Code by Anouk Geraets for doi: 10.1038/s41598-022-27368-4 Please cite this paper when using the code: Geraets, A.F.J., Leist, A.K. Sex/gender and socioeconomic differences in modifiable risk factors for dementia. Sci Rep 13, 80 (2023). https://doi.org/10.1038/s41598-022-27368-4

Data availability

The English Longitudinal Study of Ageing (ELSA) was developed by a team of researchers based at University College London, the Institute for Fiscal Studies and the National Centre for Social Research. The data are linked to the UK Data Archive and freely available through the UK data services and can be accessed here: https://discover.ukdataservice.ac.uk.

Funding

The English Longitudinal Study of Ageing is administered by a team of researchers based at the University College London, NatCen Social Research, the Institute for Fiscal Studies, and the University of Manchester. Funding is provided by National Institute on Aging (R01AG017644; principal investigator: Dr Steptoe) and by a consortium of UK government departments coordinated by the National Institute for Health Research. This work has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (Grant agreement No. 803239).

Main Code Details

We use data from Wave 1 (2002/2003) till Wave 9 (2018/2019). Since Wave 4 (2008/2009; n=9,886) includes a large number of modifiable risk factors for dementia, it was considered the baseline for this study. In case of missing information on socioeconomic status, risk factors for dementia or potential confounders, non-missing data from adjacent waves (in most cases Wave 3 (2006/2007) or Wave 5 (2010/2011) was used. The most recent data files available on September 29th, 2022, were downloaded that day. Information about the operationalization of the variables can be find in the Supplemental Material https://static-content.springer.com/esm/art%3A10.1038%2Fs41598-022-27368-4/MediaObjects/41598_2022_27368_MOESM1_ESM.pdf.

Main analyses sex/gender differences

keep if finstat4 =="C1CM" | finstat4 =="C3CM" | finstat =="C4CM"

replace w4xwgt = 0.00000001 if w4xwgt==0

stset end_dem_int [pweight = w4xwgt] if !missing(SEB_dem_prev_w9) , id(idauniq) failure(SEB_dem_prev_w9==1) enter(time date_ii4) origin(time birthdate) scale(365.25)

Total study population

stcox i.heartdisease i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.hypertension i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.cholesterol i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.diabetes i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.obesity i.indsex c.indager i. wealth_wave4_tertiles, vce(cluster `idahhw4)

stcox i.hearingloss i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.smoking i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.alcohol i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.physactivity i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.sleepdist i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.diet i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.depression i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.lowedu_c i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.socialactivity i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.cognactivity i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

Overall sex/gender difference dementia risk

stcox i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

Interaction risk factor with sex/gender

stcox i.heartdisease## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.hypertension## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.cholesterol## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.diabetes## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.obesity## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.hearingloss## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.smoking## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.alcohol## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.physactivity## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.sleepdist## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.diet## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.depression## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.lowedu_c## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.socialactivity## i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

stcox i.cognactivity##i.indsex c.indager i.wealth_wave4_tertiles, vce(cluster idahhw4)

Women

keep if indsex ==2