Study population

We used the survey and genetic data (participant study entry between 2000 and 2014) from the Chinese Longitudinal Healthy Longevity Survey (CLHLS). The CLHLS is a prospective longitudinal cohort created to explore determinants of healthy longevity in Chinese older adults. The CLHLS used a multistage, stratified cluster sampling, and recruited participants from 22 out of 31 provinces in China. With 631 cities and counties randomly selected as the sample sites, the study sample represents about 85% of the Chinese population. The survey only included the older adults aged 80 years and older in 1998 and 2000, and expanded to the older adults aged 65 years and older since the 2002 survey. The CLHLS oversampled the older adults aged 80 years and older. A more detailed description of the sampling design could be found elsewhere17. Initiated in 1998, the CLHLS conducted followed-up surveys among the survivals and recruited new participants in 2000, 2002, 2005, 2008, 2011, 2014, and 2018. CLHLS has collected extensive data, including demographic characteristics, socioeconomic status, lifestyle, physical health, psychological well-being, survival status, biomarkers, and gene17.

There were 19,726 older adults aged 65 years and older with follow-up surveys and detailed information on residential greenness. We excluded the participants who were without genetic data (n = 12,640), and were missing the SNPs of rs7412 (n = 92). We included 6,994 participants for the analysis of residential greenness, APOE ε4 status, and cognitive function.

Greenness assessment

We calculated the Normalized Difference Vegetation Index (NDVI) to reflect residential greenness. The plants absorb visible light and leaves reflect near-infrared light in the process of photosynthesis. NDVI is the ratio of the difference between the near-infrared region and red visible reflectance to the sum of these two measures. NDVI ranges from −1.0 to 1.0, with larger values indicating higher levels of vegetative density18. Different NDVI values indicate different environments. Negative values often refer to blue space or water; values of 0.1 and below reflect barren areas of rock, sand, or snow; values of 0.2 to 0.4 represent shrub and grassland; while higher values indicate temperate and tropical rainforests19.

We obtained NDVI values from the Moderate-Resolution Imaging Spectro-Radiometer (MODIS) in the National Aeronautics and Space Administration’s Terra Satellite. MODIS has a temporal resolution of 16 days. We calculated two NDVI values for January, April, July, and October between 2000 and 2014 to reflect seasonal variation in greenness. We calculated the NDVI values in the 500-m radius around the residence. We calculated the baseline annual average NDVI to indicate residential greenness at baseline. In addition, we calculated the quartiles of NDVI and 0.1-unit of NDVI values for the statistical analysis.

Cognitive function assessment

Our health outcome was cognitive function, assessed by the adapted Chinese version of Mini-Mental State Examination (MMSE). MMSE evaluated orientation, registration, attention and calculation, recall, and language20. The reliability and validity of MMSE have been demonstrated by previous studies21,22. There were 24 self-reported questions in our MMSE (Supplementary Table S1). Each question scored as zero (wrong or unable to answer) or one (correct). We converted the 24-item MMSE to a scale from 0 to 30 for consistency with other studies23,24. We categorized cognitive function into groups of having normal cognition (MMSE scores > = 24, as the reference group), and cognitive impairment (MMSE <24)25. MMSE was repeatedly measured in 2000, 2002, 2005, 2008, 2011, and 2014 during the follow-up period. We reported baseline MMSE (cognitive function at study entry) and final MMSE (cognitive function at the last available survey).

APOE ε4 status

CLHLS collected DNA samples from parts of participants in 1998, 2000, 2002, 2005, 2008–2009, and 2011–2012. Genotyping of DNA samples was produced by Beijing Genomics Institute (BGI). APOE SNPs rs429358 and rs7412 were genotyped by the Illumina HumanOmniZhongHua-8 BeadChips. This chip could profile over 900 K SNPs per sample. 98.9% of SNPs were international compatible. In the process of sample filtering, the samples whose call rate was less than 95%, identity-by-state probabilities with PI_HAT was > 0.25, and minor allele frequency was less than 1% were excluded. In addition, principal components analysis was used to test whether there was an ancestry difference among the sample participants. More details on the genotyping platform, sample filtering, and quality control can be found in Zeng et al.26. Determined by rs429358 and rs7412, there are six APOE genotypes in our participants, including ε2/ε2, ε2/ε3, ε2/ε4, ε3/ε3, ε3/ε4, and ε4/ε4. We dichotomized the participants into APOE non-ε4 carriers (including ε2/ε2, ε2/ε3, and ε3/ε3), and ε4 carriers (including ε2/ε4, ε3/ε4 and ε4/ε4).

Covariates

We assessed a number of baseline characteristics including age, gender, marital status, urban/rural residence, education, occupation, financial support, social and leisure activity, smoking status, alcohol consumption, and physical activity. We measured age based on the difference between the interview dates, and the verified birth dates. We dichotomized marital status to married and not married at the time of the interview (separated, or divorced, or widowed, or never married). We divided residence into urban areas and rural areas. Given the relatively low level of education in our participants, we defined less than one year of schooling as no formal education, and defined one year of schooling or more as some formal education. We categorized occupation into professional work (professional and technical personnel, government, and management), and non-professional work (agriculture, fishing, service, industry, and housework). We generated a binary variable for financial support, including financial independence if the participants were financially independent with their work and retirement wage, and financial dependence if they financially relied on other family members. We calculated social and leisure activity index by taking into consideration seven activities, including gardening, personal outdoor activities excluding exercise, raising poultry or pets, reading, playing cards or mah-jong, listening to the radio or watching TV, and participating in organized social activities. Each activity was scored zero (no) or one (yes), and the index ranged from zero to seven27. We categorized smoking status into never smokers as those neither smoked in the past nor at the time of the interview, former smokers as those smoked in the past but not at the time of the interview, and current smokers as those smoked at the time of the interview. We assessed alcohol consumption by using a similar definition. We dichotomized physical activity to yes and no.

Statistical analysis

We used the generalized estimating equations (GEE) to explore whether APOE ε4 carriers were at higher risks of cognitive impairment than APOE non-ε4 carriers. In addition, we also applied GEE to examine the association between baseline annual average NDVI and cognitive function. Stratified analysis by APOE ε4 status (non-ε4 carriers vs. ε4 carriers) was performed. Furthermore, we assessed the effects of annual average NDVI, APOE ε4 status, and their interaction on cognitive function by using GEE. Subgroup analysis by the age group (aged 65 to 79 years vs. aged 80 years and older) was conducted for all the analysis. All the regression models were adjusted for age, gender, marital status, urban/rural residence, education, occupation, financial support, social and leisure activity, smoking status, alcohol consumption, and physical activity, which might bias the association between residential greenness and cognitive function. Cognitive function was repeatedly assessed by using the MMSE during the follow-up period. The participants with normal cognition (MMSE > = 24) were defined as the reference group.

We calculated the odds ratio (OR), and 95% confidence intervals (CIs) to estimate the magnitude and odds of cognitive impairment, under different levels of residential greenness and APOE ε4 status. We reported the results of quartiles of NDVI and 0.1-unit of NDVI. STATA 14.0 was used for statistical analysis.

Ethical approvals

The study protocol was approved by the Institutional Review Board, Duke University (Pro00062871), and the Biomedical Ethics Committee, Peking University (IRB00001052-13074). All research was performed in accordance with relevant guidelines and regulations. Paper-based informed consent was signed and collected from all participants.