High　Density　Lipoprotein　Cholesterol　(HDL-　C)　can　effectively　promote　the　metabolic　efflux　of　cholesterol　in　human　body,　and　its　level　is　negatively　correlated　with　the　risk　of　cardiovascular　disease,　which　is　a　preventive　and　protective　factor　of　cardiovascular　disease.　It　is　of　great　significance　to　clarify　the　geographical　characteristics　and　environmental　factors　of　HDL-C　level　in　middle-aged　and　elderly　population　in　China.　Based　on　the　longitudinal　survey　of　middle-　aged　and　elderly　people　in　China,　this　paper　uses　global　spatial　autocorrelation　and　cold　hot　spot　analysis　to　explain　the　spatial　characteristics　and　trends　of　HDL-C　levels　in　middle-　aged　and　elderly　people　in　China.　At　the　same　time,　the　random　forest　regression　model　and　multiple　linear　regression　method　are　compared　to　explore　the　environmental　factors　influencing　the　spatial　distribution　of　HDL-C　level.　The　results　show　that　the　HDL-C　level　of　middle-aged　and　elderly　population　in　China　is　higher　in　females　than　that　in　males,　and　higher　in　rural　areas　than　that　in　urban　areas,　with　obvious　regional　differences.　The　overall　distribution　pattern　is　＇low　in　the　north　and　high　in　the　south,　with　transition　in　the　middle＇.　In　addition,　there　are　low　value　aggregation　areas　in　Inner　Mongolia,　Hebei,　and　Liaoning　in　the　north　and　high　value　aggregation　areas　in　Guangdong,　Guangxi,　and　Yunnan　in　the　south.　The　SO2,　NO2,　precipitation,　air　pressure,　PM10　and　PM2.5　are　the　main　environmental　factors　affecting　the　different　distributions　of　HDL-C　level　in　middle-aged　and　elderly　population.　Among　them,　high　concentration　of　air　pollutants　is　the　risk　factor　of　low　HDL-C　value,　while　abundant　precipitation　and　low-pressure　environment　are　the　protective　factors　to　prevent　and　control　low　HDL-　C　value.　Therefore,　the　prevention　and　control　of　HDL-　C　dyslipidemia　should　pay　attention　to　its　spatial　distribution　throughout　the　country　in　the　future,　focusing　on　strengthening　the　monitoring　of　HDL-C　low　value　areas,　so　as　to　achieve　the　purpose　of　adjusting　measures　to　local　conditions　and　accurate　prevention　and　control.　©　2022,　Science　Press.　All　right　reserved.