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    ๊ตญ๋ฏผ์—ฐ๊ธˆ ์ˆ˜๊ธ‰์—ฌ๋ถ€๊ฐ€ ์€ํ‡ด๊ฐ€๊ณ„์˜ ์†Œ๋น„์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ํ–‰์ •๋Œ€ํ•™์› ๊ณต๊ธฐ์—…์ •์ฑ…ํ•™๊ณผ, 2021.8. ์ตœํƒœํ˜„.๊ตญ๋ฏผ์—ฐ๊ธˆ์ œ๋„๋Š” ๋…ธ๋ น ๋“ฑ์œผ๋กœ ์†Œ๋“๊ฐ์†Œ์‹œ ์—ฐ๊ธˆ๊ธ‰์—ฌ๋ฅผ ์ง€๊ธ‰ํ•จ์œผ๋กœ์จ ์ƒํ™œ์•ˆ์ •๊ณผ ๋ณต์ง€์ฆ์ง„์„ ๋„๋ชจํ•˜๋Š” ์šฐ๋ฆฌ๋‚˜๋ผ์˜ ๋Œ€ํ‘œ์ ์ธ ์‚ฌํšŒ๋ณด์žฅ์ œ๋„์ด๋‹ค. ์„ ํ–‰์—ฐ๊ตฌ๋“ค์€ ๋Œ€์ฒด๋กœ ๊ตญ๋ฏผ์—ฐ๊ธˆ์›”์•ก์„ ๊ธฐ์ค€์œผ๋กœ ๋นˆ๊ณค์™„ํ™”, ์†Œ๋“์žฌ๋ถ„๋ฐฐ, ์†Œ๋“๋ณด์žฅ ์ •๋„๋ฅผ ํ†ตํ•ด ์ •์ฑ…์˜ ํšจ๊ณผ๋ฅผ ์ธก์ •ํ•œ ๋ฐ”, ๋ณธ ์—ฐ๊ตฌ๋Š” ์†Œ๋น„์™€ ๊ฐ™์€ ์ƒํ™œ์ˆ˜์ค€์˜ ์ ‘๊ทผ์ด ๋ณต์ง€์— ๋Œ€ํ•œ ์ง์ ‘์  ์ธก์ •์ด๋ผ๊ณ  ํ•œ Ringen(1997)์˜ ์ด๋ก ์„ ๋”ฐ๋ผ ์—ฐ๊ธˆ์ˆ˜๊ธ‰์ด ์‹ค์ œ ์ƒํ™œ์ˆ˜์ค€์— ์–ด๋– ํ•œ ๋ณ€ํ™”๋ฅผ ๊ฐ€์ ธ์™”๋Š”์ง€๋ฅผ ์†Œ๋น„์ง€์ถœ์„ ํ†ตํ•ด ์ธก์ •ํ•˜๋Š” ๋ณต์ง€์˜ ์ง์ ‘ ์ธก์ •๋ฐฉ์‹์œผ๋กœ ์ •์ฑ…์˜ ํšจ๊ณผ๋ฅผ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋จผ์ €, ์€ํ‡ด์ „ํ›„์˜ ์†Œ๋น„์ง€์ถœ์„ ํ†ตํ•ด ์ผ๋ฐ˜์ ์ธ ์ง€์ถœํŒจํ„ด์„ ์‚ดํŽด๋ณด๊ณ , ๋‹ค์Œ์œผ๋กœ ์—ฐ๊ธˆ ์ˆ˜๊ธ‰์ˆ˜์ค€์— ๋”ฐ๋ฅธ ์ด์†Œ๋น„์ง€์ถœ, ๊ฐœ๋ณ„ ํ•ญ๋ชฉ๋ณ„ ์ˆ˜์ค€์„ ์‚ดํŽด๋ณด์•˜์œผ๋ฉฐ, ์†Œ๋“๊ณผ ์†Œ๋น„์˜ ๋น„์œจ์„ ํ†ตํ•ด ๊ฐ€๊ตฌ์˜ ์†Œ๋“์ ์ •์„ฑ์„ ์ธก์ •ํ•˜์˜€๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ๊ตญ๋ฏผ๋…ธํ›„๋ณด์žฅ ํŒจ๋„์กฐ์‚ฌ์˜ 4โˆผ7์ฐจ ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•˜์˜€์œผ๋ฉฐ ํŒจ๋„ํšŒ๊ท€๋ถ„์„๊ณผ ํŒจ๋„๋กœ์ง“๋ถ„์„์„ ๋ถ„์„๋ฐฉ๋ฒ•์œผ๋กœ ์„ ํƒํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ, ๊ตญ๋ฏผ์—ฐ๊ธˆ ์ˆ˜๊ธ‰์ˆ˜์ค€์ด ๋†’์„์ˆ˜๋ก ์ด ์†Œ๋น„์ง€์ถœ์ด ์ฆ๊ฐ€ํ•˜๋Š” ํšจ๊ณผ๋ฅผ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ ๊ฐœ๋ณ„ ์†Œ๋น„ํ•ญ๋ชฉ์—์„œ๋Š” ์‹๋น„์™€ ๋ณด๊ฑด์˜๋ฃŒ๋น„๊ฐ€ ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ํšจ๊ณผ๋Š” ์†Œ๋“์ˆ˜์ค€์ด ๋‚ฎ์€ ๊ฐ€๊ตฌ์—์„œ ๋‘๋“œ๋Ÿฌ์ง€๊ฒŒ ๋‚˜ํƒ€๋‚˜ ๊ตญ๋ฏผ์—ฐ๊ธˆ ์ •์ฑ…์ด ์†Œ๋“์ด ๋‚ฎ์€ ๊ฐ€๊ตฌ์˜ ์†Œ๋น„๋ฅผ ์ง„์ž‘์‹œํ‚ค๋Š” ํšจ๊ณผ๊ฐ€ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์†Œ๋“ ์ ์ •์„ฑ์—์„œ๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜๋ฏธํ•˜์ง€๋Š” ์•Š์•˜์ง€๋งŒ ๊ตญ๋ฏผ์—ฐ๊ธˆ ์ˆ˜๊ธ‰์ˆ˜์ค€์ด ๋†’์„์ˆ˜๋ก ์ ์ •์„ฑ์ด ํ•˜๋ฝํ•˜๋Š” ํ˜„์ƒ์ด ๊ด€์ฐฐ๋˜์—ˆ๋‹ค. ์ด๋Š” ์†Œ๋“์ˆ˜์ค€์ด ๋น„์Šทํ•˜๋”๋ผ๋„ ๊ตญ๋ฏผ์—ฐ๊ธˆ ์ˆ˜๊ธ‰์ˆ˜์ค€์ด ๋†’์„์ˆ˜๋ก ์†Œ๋น„๊ฐ€ ์ฆ๊ฐ€ํ•˜๋Š” ํ˜„์ƒ์— ๋”ฐ๋ฅธ ๊ฒƒ์œผ๋กœ ๋ณด์—ฌ์ง„๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์†Œ๋“์›์˜ ํŠน์„ฑ์— ๋”ฐ๋ผ ์†Œ๋“๊ณผ ์†Œ๋น„์™€์˜ ์—ฐ๊ณ„์ •๋„๊ฐ€ ๋‹ค๋ฅผ ์ˆ˜ ์žˆ์Œ์„ ์ถ”์ •ํ•˜์˜€๋‹ค. ๊ตญ๋ฏผ์—ฐ๊ธˆ์€ ๋งค์›” ๊ณ ์ •์ ์ธ ์ˆ˜์ค€์˜ ๊ธ‰์—ฌ๊ฐ€ ์ˆ˜๊ธ‰์š”๊ฑด์ด ํ•ด์†Œ๋  ๋•Œ๊นŒ์ง€, ์ผ๋ฐ˜์ ์œผ๋กœ ์‚ฌ๋ง์‹œ๊นŒ์ง€ ์ง€๊ธ‰๋˜๋ฏ€๋กœ ๋ถ€๋™์‚ฐ, ๊ธˆ์œต ๋“ฑ๋‹ค๋ฅธ ์†Œ๋“์›์— ๋น„ํ•ด ์†Œ๋น„์™€์˜ ์—ฐ๊ณ„์ •๋„๊ฐ€ ๋†’์„ ๊ฒƒ์ด๋ผ ์ถ”์ •ํ•  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์†Œ๋น„์ง€์ถœ์„ ํ†ตํ•ด ๊ตญ๋ฏผ์—ฐ๊ธˆ์˜ ์ •์ฑ…์  ํšจ๊ณผ๋ฅผ ์‹ค์ฆํ•˜์˜€๋‹ค๋Š” ์ ์— ์˜์˜๋ฅผ ๊ฐ€์ง€๋ฉฐ ๊ตญ๋ฏผ๋“ค์ด ์ผ์ •์ˆ˜์ค€์˜ ๊ฐ€์ฒ˜๋ถ„ ์†Œ๋“์„ ์œ ์ง€ํ•  ์ˆ˜ ์žˆ๋„๋ก ๊ตญ๋ฏผ์—ฐ๊ธˆ์ œ๋„๋ฅผ ๊ฐ•ํ™”์‹œํ‚ค๋Š” ๋ฐฉ์•ˆ์„ ์ œ์•ˆํ•˜์˜€๋‹ค.Following Ringen (1997)'s theory that the measures such as consumption is a direct measure of welfare, This study analyzed the effect of policy as a direct measure of welfare through consumption expenditure. My study looked at the general spending patterns before and after retirement, then focus on the consumption expenditure based on the levels on national pension. And measured the income adequacy of households through the ratio of income to consumption. According to the analysis, the higher the national pension level, the higher the total consumption expenditure, and the higher food expense and health and medical expenses for individual consumption items. This effect was noticeable in households with low income levels, confirming that the national pension policy has the effect of boosting consumption of households with low income. Although it was not statistically significant in income adequacy, it was observed that the higher the national pension level, the lower the adequacy. This seems to be due to the phenomenon in which consumption increases as the level of national pension is higher, even if the income level is similar. Through this, it was estimated that the degree of link between income and consumption may vary depending on the characteristics of income sources. The National Pension benefits can be estimated to have a higher degree of link with consumption than other sources of income, such as real estate and finance, as it is usually paid until the supply and demand requirements are resolved every month and until death.์ œ1์žฅ ์„œ๋ก  1 ์ œ1์ ˆ ์—ฐ๊ตฌ์˜ ํ•„์š”์„ฑ ๋ฐ ๋ชฉ์  1 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ๋Œ€์ƒ ๋ฐ ๋ฐฉ๋ฒ• 4 ์ œ2์žฅ ์ด๋ก ์  ๋…ผ์˜์™€ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  6 ์ œ1์ ˆ ์ด๋ก ์  ๋…ผ์˜ 6 ์ œ2์ ˆ ์„ ํ–‰์—ฐ๊ตฌ ๊ฒ€ํ†  17 ์ œ3์ ˆ ์†Œ๊ฒฐ 33 ์ œ3์žฅ ์—ฐ๊ตฌ์˜ ์„ค๊ณ„ 34 ์ œ1์ ˆ ๋ถ„์„์˜ ํ‹€ 34 ์ œ2์ ˆ ๋ถ„์„๋ฐฉ๋ฒ• 36 ์ œ3์ ˆ ๋ถ„์„๋Œ€์ƒ 37 ์ œ4์ ˆ ๋ถ„์„๋ณ€์ˆ˜ 38 ์ œ4์žฅ ๋ถ„์„ ๊ฒฐ๊ณผ 42 ์ œ1์ ˆ ๊ธฐ์ดˆ ํ†ต๊ณ„๋Ÿ‰ 42 ์ œ2์ ˆ ์ง‘๋‹จ๊ฐ„ ์ฐจ์ด๋ถ„์„ 47 ์ œ3์ ˆ ํŒจ๋„ํšŒ๊ท€ ๋ฐ ํŒจ๋„๋กœ์ง“ ๋ถ„์„ 52 ์ œ5์žฅ ๊ฒฐ๋ก  68 ์ œ1์ ˆ ๋ถ„์„๊ฒฐ๊ณผ ์š”์•ฝ 68 ์ œ2์ ˆ ์—ฐ๊ตฌ์˜ ํ•จ์˜ ๋ฐ ํ•œ๊ณ„ 70์„

    Relationship between depression and family values in married women :

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    ๋ณด๊ฑด์ •์ฑ…ํ•™๊ณผ/์„์‚ฌ๊ธฐํ˜ผ์—ฌ์„ฑ์˜ ์šฐ์šธ์€ ๋‹จ์ˆœํžˆ ๊ฐœ์ธ์˜ ์ฐจ์›์„ ๋„˜์–ด์„œ ๊ฐ€์ •์˜ ๋‹ค๋ฅธ ๊ฐ€์กฑ ๊ตฌ์„ฑ์›์—๊ฒŒ ๋ถ€์ •์ ์ธ ์˜ํ–ฅ์„ ์ง์ ‘์ ์œผ๋กœ ๋ฏธ์นœ๋‹ค. ์—ฌ์„ฑ์˜ ์šฐ์šธ๊ณผ ๊ด€๋ จํ•œ ์„ ํ–‰์—ฐ๊ตฌ๋Š” ๊ฐ€์ •๊ณผ ์‚ฌํšŒ์  ์ง€์ง€์— ์ดˆ์ ์„ ๋งž์ถฐ ์ง„ํ–‰๋˜์–ด ์™”๋‹ค. ์ด์— ๋ณธ ์—ฐ๊ตฌ๋Š” ์—ฌ์„ฑ์˜ ์‚ถ์˜ 1์ฐจ์  ํ™˜๊ฒฝ์ธ ๊ฐ€์กฑ์— ๋Œ€ํ•œ ์ฃผ์š”ํ•œ ์‹ฌ๋ฆฌํŠน์„ฑ ์š”์ธ์ด์ž ์‚ฌํšŒ์™€ ๊ฐ€์กฑ๊ตฌ์กฐ๋ฅผ ์—ฐ๊ตฌํ•˜๋Š”๋ฐ ๋งค์šฐ ์ „๋žต์ ์ธ ์œ„์น˜๋ฅผ ์ฐจ์ง€ํ•˜๋Š” ๊ฐœ๋…์ธ ๊ฐ€์กฑ๊ฐ€์น˜๊ด€์— ์ฃผ๋ชฉํ•˜์—ฌ ๊ธฐํ˜ผ์—ฌ์„ฑ์˜ ์šฐ์šธ๊ณผ์˜ ๊ด€๋ จ์„ฑ์„ ํŒŒ์•…ํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ํ•œ๊ตญ์—ฌ์„ฑ์ •์ฑ…์—ฐ๊ตฌ์›์—์„œ ์‹œํ–‰ํ•œ ์—ฌ์„ฑ๊ฐ€์กฑํŒจ๋„์กฐ์‚ฌ(Korean Longitudinal Survey of Women and Families: KLoWF) ์ œ 4์ฐจ ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๊ธฐํ˜ผ ์—ฌ์„ฑ 5,818๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ธฐํ˜ผ์—ฌ์„ฑ์˜ ์šฐ์šธ๊ณผ ๊ด€๋ จ๋œ ์„ ํ–‰์—ฐ๊ตฌ๋ฅผ ์ฐธ๊ณ ํ•˜์—ฌ ๋…๋ฆฝ๋ณ€์ˆ˜๋ฅผ ์„ ์ •ํ•˜์˜€๋‹ค. ๊ทธ ๊ฒฐ๊ณผ ๊ฐ€์กฑ๊ฐ€์น˜๊ด€ ์š”์ธ, ๊ฐ€์ • ์š”์ธ, ์ธ๊ตฌ์‚ฌํšŒ์š”์ธ์„ ์„ ์ •ํ•˜์˜€์œผ๋ฉฐ, ๊ธฐ์ˆ ๋ถ„์„, ๋‹จ๋ณ€์ˆ˜ ๋ถ„์„์œผ๋กœ Chi-squeare ๊ฒ€์ •, ๋‹ค๋ณ€์ˆ˜ ๋ถ„์„์œผ๋กœ Logistic regression ๋ถ„์„์„ ์‹ค์‹œํ•˜์˜€๋‹ค. ๊ฐ€์ • ์š”์ธ๊ณผ ์ธ๊ตฌ์‚ฌํšŒ์š”์ธ์„ ํ†ต์ œํ•˜์˜€์„ ๋•Œ์— ๊ฐ€์กฑ๊ฐ€์น˜๊ด€ ์š”์ธ์˜ ์˜ํ–ฅ๋ ฅ์„ ํŒŒ์•…ํ•˜๊ธฐ ์œ„ํ•˜์—ฌ ใ€Ž๋ชจ๋ธ 1ใ€,ใ€Ž๋ชจ๋ธ 2ใ€,ใ€Ž๋ชจ๋ธ 3ใ€์„ ํ†ตํ•ด ๊ฐ€์กฑ๊ฐ€์น˜๊ด€ ์š”์ธ, ๊ฐ€์ • ์š”์ธ, ์ธ๊ตฌ์‚ฌํšŒ ์š”์ธ์„ ๋‹จ๊ณ„๋ณ„๋กœ ํ†ต์ œํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๊ฒฐ๊ณผ, ๊ฐ€์กฑ๊ฐ€์น˜๊ด€ ์š”์ธ์€ ใ€Ž๋ชจ๋ธ 1ใ€์—์„œ ใ€Ž๋ชจ๋ธ 3ใ€์œผ๋กœ ์ง„ํ–‰๋ ์ˆ˜๋ก ๊ธฐํ˜ผ์—ฌ์„ฑ์˜ ์šฐ์šธ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ๋ ฅ์ด ์ ์ฐจ ํ™•๋Œ€๋˜์–ด ๊ธฐํ˜ผ์—ฌ์„ฑ์˜ ์šฐ์šธ์„ ์˜ˆ์ธกํ•  ์ˆ˜ ์žˆ๋Š” ๊ฐ•๋ ฅํ•œ ์š”์ธ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ๊ธฐํ˜ผ์—ฌ์„ฑ์€ ๊ฐ€์กฑ์ฃผ์˜์  ๊ฒฐํ˜ผ๊ด€์ด ๊ฐ•ํ• ์ˆ˜๋ก ์šฐ์šธ ๊ฒฝํ—˜์ด ๊ฐ์†Œํ•˜๊ณ , ๊ฐœ์ธ์ฃผ์˜์  ๊ฒฐํ˜ผ๊ด€์ด ๊ฐ•ํ• ์ˆ˜๋ก ์šฐ์šธ๊ฒฝํ—˜์ด ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. ์ฆ‰, ๊ธฐํ˜ผ์—ฌ์„ฑ์€ ๊ฒฐํ˜ผ๊ณผ ์ž๋…€, ์ดํ˜ผ์— ๋Œ€ํ•œ ๊ฐ€์น˜๊ด€์˜ ์ „ํ†ต์„ฑ์ด ์•ฝํ• ์ˆ˜๋ก ์šฐ์šธ๊ฒฝํ—˜์ด ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋ฐ˜๋ฉด, ์ „ํ†ต์  ๋ถ€๋ถ€์—ญํ• ๊ด€์€ ๊ทธ ์„ฑํ–ฅ์ด ๊ฐ•ํ• ์ˆ˜๋ก ์šฐ์šธ๊ฒฝํ—˜์ด ์ฆ๊ฐ€ํ•˜์˜€๋‹ค. ๊ฒฐํ˜ผ๊ด€์€ ๊ฐœ์ธ์ฃผ์˜์  ์„ฑํ–ฅ์ด ๊ฐ•ํ•˜๋ฉด์„œ๋„ ๋ถ€๋ถ€์—ญํ• ์— ๋Œ€ํ•œ ๊ฐ€์น˜๊ด€์€ ์ „ํ†ต์„ฑ์ด ๊ฐ•ํ•œ ๊ธฐํ˜ผ์—ฌ์„ฑ์ด ์šฐ์šธ์˜ ๊ฒฝํ—˜์ด ๋†’์€ ๊ฒƒ์œผ๋กœ, ๊ธฐํ˜ผ์—ฌ์„ฑ์—์„œ ๊ฒฐํ˜ผ๊ด€๊ณผ ๋ถ€๋ถ€์—ญํ• ๊ด€์€ ์„œ๋กœ ์ƒ์ถฉ๋˜๋Š” ๊ฒƒ์œผ๋กœ ํ•ด์„ํ•  ์ˆ˜ ์žˆ๋‹ค. ๊ฐ€์ • ์š”์ธ๊ณผ ์ธ๊ตฌ์‚ฌํšŒ ์š”์ธ์œผ๋กœ๋Š” 1๋…„๊ฐ„ ๊ฐ€๊ตฌ์ด์†Œ๋“์ด ๋‚ฎ๊ณ , ๋‚จํŽธ ์—ฐ๋ น์ด ๋งŽ์œผ๋ฉฐ, ๊ฐ€์‚ฌ๋…ธ๋™๋ถ„๋‹ด์— ๋ถˆ๋งŒ์กฑํ•˜๊ณ  ๊ฐˆ๋“ฑ์ƒํ™ฉ ์ค‘ ํŠนํžˆ ์‹œ๋ถ€๋ชจ, ์นœ์ •๋ถ€๋ชจ์™€์˜ ๊ด€๊ณ„๋กœ ๊ฐˆ๋“ฑ์„ ๊ฒช์œผ๋ฉฐ, ์ฃผ๊ด€์  ๊ฑด๊ฐ•์ด ๋‚˜์œ ์ง‘๋‹จ์ด ์šฐ์šธ ๊ฒฝํ—˜์ด ๋†’์•˜๋‹ค. ๋ฐ˜๋Œ€๋กœ, ๋‚จํŽธ์˜ ์ง์ข…์ด ์„œ๋น„์Šค, ํŒ๋งค ์ข…์‚ฌ์ž๊ฑฐ๋‚˜, ์—ฌ์„ฑ์˜ ์ง์ข…์ด ๋†์ž„์–ด์—… ์ข…์‚ฌ์ž์ธ ๊ฒฝ์šฐ๋Š” ๋ฌด์ง์ธ ์ง‘๋‹จ์— ๋น„ํ•ด ์šฐ์šธ ๊ฒฝํ—˜์ด ๋‚ฎ์€ ๊ฒƒ์œผ๋กœ ์กฐ์‚ฌ๋˜์—ˆ๋‹ค. ์ด ์—ฐ๊ตฌ๋Š” ๊ธฐํ˜ผ ์—ฌ์„ฑ์„ ๋Œ€์ƒ์œผ๋กœ ๊ฐ€์ • ์š”์ธ๊ณผ ์ธ๊ตฌ์‚ฌํšŒ ์š”์ธ์„ ์ˆœ์ฐจ์ ์œผ๋กœ ํ†ต์ œํ•œ ์ƒํƒœ์—์„œ ๊ฒฐํ˜ผ๊ณผ ์ž๋…€, ์ดํ˜ผ, ๊ฐ€์ • ๋‚ด ๋ถ€๋ถ€์—ญํ•  ๋“ฑ ๊ฐ€์กฑ์— ๋Œ€ํ•œ ํฌ๊ด„์ ์ธ ๊ฐ€์กฑ๊ฐ€์น˜๊ด€๊ณผ ์šฐ์šธ๊ณผ์˜ ๊ด€๋ จ์„ฑ ๋ณ€ํ™”๋ฅผ ๋ถ„์„ํ•œ ์ฒซ ์—ฐ๊ตฌ์ด๋‹ค. ์—ฐ๊ตฌ ๊ฒฐ๊ณผ๋ฅผ ํ† ๋Œ€๋กœ ๊ฐ€์กฑ๊ฐ€์น˜๊ด€์˜ ๊ฐœ์ธ์ฃผ์˜์  ์„ฑํ–ฅ์ด ๊ฐ•ํ•œ ์—ฌ์„ฑ์˜ ์šฐ์šธ ๊ฒฝํ—˜์ด ๋†’์€ ๊ฒƒ์— ์ฃผ๋ชฉํ•˜์—ฌ ๋‹ค์–‘ํ•œ ๊ฐ€์กฑ ํ˜•ํƒœ ๋ฐ ์—ฌ์„ฑ์˜ ๊ฐœ์ธ์˜ ์„ฑ์ทจ์™€ ์‚ฌํšŒ๊ฒฝ์ œํ™œ๋™์„ ์ง€์ง€ํ•˜๋Š” ์‚ฌํšŒ๋ถ„์œ„๊ธฐ์˜ ์ „ํ™˜ ๋ฐ ์ด๋ฅผ ๊ฐ€๋Šฅ์ผ€ ํ•˜๋Š” ์ •์ฑ…์  ๊ฐœ์ž…์ด ํ•„์š”ํ•  ๊ฒƒ์ด๋‹ค. ๋˜ํ•œ, ์‚ฌํšŒ๊ฒฝ์ œ์  ์ง€์œ„๊ฐ€ ๋‚ฎ์€ ๊ณ„์ธต์˜ ์šฐ์šธ์„ ์™„ํ™”ํ•˜๊ธฐ ์œ„ํ•œ ํƒ€๊นƒ ์ง€ํ–ฅ์  ํ”„๋กœ๊ทธ๋žจ, ๋ถ€๋ถ€์™€ ๊ฐ€์กฑ์ด ํ•จ๊ป˜ ์ฐธ์—ฌํ•˜์—ฌ ์—ฌ์„ฑ์˜ ์šฐ์šธ ๊ฐ์†Œ๋ฅผ ์œ„ํ•ด ๋‚จํŽธ๊ณผ ๊ฐ€์กฑ์˜ ์ง€์ง€๋ฅผ ์ด๋Œ์–ด ๋‚ผ ์ˆ˜ ์žˆ๋Š” ์ง€์—ญ์‚ฌํšŒ ๊ธฐ๋ฐ˜ ์ •์‹ ๊ฑด๊ฐ•์ฆ์ง„ ํ”„๋กœ๊ทธ๋žจ์ด ํ•„์š”ํ•˜๊ฒ ๋‹ค.ope

    Individual and regional factors influencing the prevalence of depressive symptoms in single-person households

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    Backgounds According to the Ministry of Public Administration and Security's 'Resident Registration Demographics', the number of single-person households nationwide, which was 35% in 2016, was 9,063,362 as of the end of 2020, accounting for 39.2% of the total number of household members. The proportion of single-person households is expected to gradually increase due to the rise in the age of marriage, changes in the perception of non-marriage, changes in lifestyles in which drinking alone and eating alone, maintaining the low fertility trend, increasing divorce rates, aging population, and progress in urbanization. A low quality residential environment is a direct factor that lowers the quality of life of single-person households. According to the announcement of the Korea Real Estate Board, house prices nationwide have increased by 10.75% for about four years since May 2017. By housing type, house prices rose by 12.01% for apartments, 12.34% for detached houses, and 2.69% for row houses. As housing price is a factor that directly affects housing cost, this study considers that regional factors related to housing cost affect the living environment and satisfaction of single-person households, and that it is also related to the prevalence of depression among individuals in relation to housing stability. Methods Data corresponding to an adult single-person household was extracted using the 2019 Community Health Survey data, which is a survey data of 255 cities, counties, and wards across the country, and used as data at the individual level. Data at the regional level are obtained through the KOSIS(Korea Statistical Information Service), the e-local index system, and the National Housing Price Trend Survey by the Korea Real Estate Board. Apartment monthly rent price index, land price change rate, house sale price change rate, single-person household ratio, single-person household ownership ratio, housing sale price index, and Jeonse price ratio to sales price were used. Through the calculation of the total score of the Depression Screening Tool (PHQ-9:Patient Health Questionnaire-9) of the Community Health Survey, if the score was 10 or higher, the prevalence of depression was considered as the dependent variable. The study subjects were 21,588 adults in single-person households with measurable prevalence of depression, a dependent variable, in 156 regions where regional-level variables were measurable at the city/gun/gu level. Consideration, factors affecting the prevalence of depressive symptoms were analyzed. Results Of the total 21,588 subjects, 8,358 males and 13,230 females were the most common, with 9,737 (45.32%) over 65 years of age and the lowest with 3,084 (14.35%) aged 19-35. The prevalence of depression with a PHQ-9 score of more than 10 was 1,366, or 6.33% of the total study subjects. Variables with correlation were identified through correlation analysis between individual and regional level variables. Finally, 11 individual level variables and 7 regional level variables were input and analyzed. As a result of the basic model analysis, among the factors affecting the prevalence of depressive symptoms in adults in single-person households, the explanatory power at the regional level was 6.41%, confirming that multi-level analysis was possible, and applying this result, the following results were derived. Among the individual level factors included in the analysis, gender, age, recipients of basic livelihood and monthly average income were significant variables. This was found to be a significant variable, and at the regional level, the apartment jeonse price index, the apartment monthly rent price index, the housing sale price change rate and the home ownership ratio of single-person households were found to be significant variables. In other words, when other conditions were constant, the odds ratio for depression was higher for women compared to men, for young adults (19-35 years old), and for recipients of Basic Livelihood Security. , divorce, bereavement, separation, and other spouse loss states, the odds ratio of the prevalence of depression was higher. In terms of health behavior-related factors, the odds ratio of the prevalence of depression was very high in the case of daily smoking, the non-exercise compared to the group who practiced moderate or more physical activity, and the subjectively poor health status. As an interesting result considering regional-level variables, the odds ratio of the prevalence of depression decreased (0.97) as the apartment jeonse price index increased, and the odds ratio of the prevalence of depression increased (1.08) as the monthly rent price index increased. Conclusions This study is a study that analyzed factors affecting the prevalence of depressive symptoms in consideration of regional level variables related to individual and city/gun/gu unit housing cost targeting adult single-person households nationwide. was able to identify significant influencing factors. In the future, it is expected that it can be used as basic data to understand the correlation between regional level housing cost-related variables and individuals' prevalence of depression or subjective health status by using more diverse and specific regional-level variables. ์—ฐ๊ตฌ๋ฐฐ๊ฒฝ ํ–‰์ •์•ˆ์ „๋ถ€ โ€˜์ฃผ๋ฏผ๋“ฑ๋ก ์ธ๊ตฌํ†ต๊ณ„'์— ๋”ฐ๋ฅด๋ฉด โ€˜16๋…„ ์ „์ฒด 35%์˜€๋˜ ์ „๊ตญ 1์ธ๊ฐ€๊ตฌ ์ˆ˜๋Š”โ€˜20๋…„ ๋ง ๊ธฐ์ค€ 906๋งŒ 3,362๊ฐ€๊ตฌ๋กœ ์ „์ฒด ๊ฐ€๊ตฌ์›์ˆ˜์˜ 39.2%์— ๋‹ฌํ–ˆ์œผ๋ฉฐ ๋ฐ˜๋ฉด ์ด์ „์— ๋ณดํŽธํ™”๋œ ํ•ต๊ฐ€์กฑ ํ˜•ํƒœ์˜€๋˜ 4์ธ ๊ฐ€๊ตฌ๋Š” ์ ์ฐจ ๊ฐ์†Œ์ถ”์„ธ์ด๋‹ค. ํ˜ผ์ธ์—ฐ๋ น์˜ ์ƒ์Šน, ๋น„ํ˜ผ์— ๋Œ€ํ•œ ์ธ์‹๋ณ€ํ™”, ํ˜ผ์ˆ , ํ˜ผ๋ฐฅ ๋“ฑ์ด ๋ณดํŽธํ™”๋œ ์ƒํ™œํ˜•ํƒœ์˜ ๋ณ€ํ™”, ์ €์ถœ์‚ฐ ๊ธฐ์กฐ์˜ ์œ ์ง€, ์ดํ˜ผ๋ฅ  ์ฆ๊ฐ€, ์ธ๊ตฌ ๊ณ ๋ นํ™”, ๋„์‹œํ™”์˜ ์ง„์ „์œผ๋กœ ์ธํ•ด 1์ธ๊ฐ€๊ตฌ์˜ ๋น„์œจ์€ ์ ์ฐจ ๋Š˜์–ด๋‚  ๊ฒƒ์œผ๋กœ ์ „๋ง๋œ๋‹ค. ์งˆ์ ์œผ๋กœ ๋‚ฎ์€ ์ฃผ๊ฑฐํ™˜๊ฒฝ์ˆ˜์ค€์€ 1์ธ๊ฐ€๊ตฌ์˜ ์‚ถ์˜ ์งˆ์„ ๋‚ฎ์ถ”๋Š” ์ง์ ‘์  ์š”์ธ์ด ๋˜๋Š”๋ฐ, ํ•œ๊ตญ๋ถ€๋™์‚ฐ์›์˜ ๋ฐœํ‘œ์— ๋”ฐ๋ฅด๋ฉด 2017๋…„ 5์›” ์ดํ›„ ์ „๊ตญ์˜ ์ง‘๊ฐ’์€ ์•ฝ 4๋…„๊ฐ„ 10.75% ์ƒ์Šนํ•˜์˜€์œผ๋ฉฐ ์ฃผํƒ์œ ํ˜•๋ณ„๋กœ๋Š” ์•„ํŒŒํŠธ 12.01%, ๋‹จ๋…์ฃผํƒ 12.34%, ์—ฐ๋ฆฝ์ฃผํƒ์€ 2.69% ์ง‘๊ฐ’์ด ์ƒ์Šนํ•˜์˜€๊ณ  ์ง€์—ญ๋ณ„๋กœ๋Š” ์„œ์šธ์ด 15.39%, ์ˆ˜๋„๊ถŒ ์ „์ฒด๋Š” 17% ์ƒ์Šนํ•˜๋Š” ๋“ฑ ๊ฐ€ํŒŒ๋ฅธ ์ƒ์Šน์„ธ๋ฅผ ๋ณด์˜€๋‹ค. ์ˆ˜๋„๊ถŒ ์™ธ ์ง€๋ฐฉ์—์„œ๋„ ์ „๊ตญ ์ตœ๊ณ  ์ƒ์Šน๋ฅ ์„ ๋ณด์ธ ์„ธ์ข…์‹œ๋Š” 47.50%, ๋Œ€์ „ 32.16%๋ฅผ ๋‚˜ํƒ€๋‚ด๋Š” ๋“ฑ ์ง€์—ญ์  ํŠน์„ฑ์— ๋”ฐ๋ผ ๋ณด๋‹ค ๋” ๋†’์€ ์ƒ์Šน๋ฅ ์„ ๋ณด์ด๋Š” ๊ณณ๋„ ์žˆ์—ˆ๋‹ค. ์ฃผํƒ๊ฐ€๊ฒฉ์€ ์ฃผ๊ฑฐ๋น„์— ์ง์ ‘์ ์ธ ์˜ํ–ฅ์„ ์ฃผ๋Š” ์š”์ธ์œผ๋กœ, ์ฃผ๊ฑฐ๋น„ ๊ด€๋ จ ์ง€์—ญ์ ์ธ ์š”์ธ์ด 1์ธ๊ฐ€๊ตฌ์˜ ์ฃผ๊ฑฐํ™˜๊ฒฝ ๋ฐ ๋งŒ์กฑ๋„์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๊ณ , ์ฃผ๊ฑฐ์•ˆ์ •๊ณผ ๊ด€๋ จํ•˜์—ฌ ๊ฐœ์ธ์˜ ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘๊ณผ๋„ ๊ด€๋ จ์ด ์žˆ์„ ๊ฒƒ์ด๋ผ๊ณ  ์ƒ๊ฐํ•˜์—ฌ ๋ณธ ์—ฐ๊ตฌ๋ฅผ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• ์ „๊ตญ 255๊ฐœ ์‹œยท๊ตฐยท๊ตฌ ๋‹จ์œ„์˜ ์กฐ์‚ฌ ์ž๋ฃŒ์ธ 2019๋…„๋„ ์ง€์—ญ์‚ฌํšŒ๊ฑด๊ฐ•์กฐ์‚ฌ ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ์„ฑ์ธ 1์ธ๊ฐ€๊ตฌ์— ํ•ด๋‹นํ•˜๋Š” ์ž๋ฃŒ๋ฅผ ์ถ”์ถœํ•˜์˜€๊ณ , ์ด๋ฅผ ๊ฐœ์ธ ์ˆ˜์ค€์˜ ์ž๋ฃŒ๋กœ ํ™œ์šฉํ•˜์˜€๋‹ค. ์ง€์—ญ์ˆ˜์ค€์˜ ์ž๋ฃŒ๋Š” ํ†ต๊ณ„์ฒญ ๊ตญ๊ฐ€ํ†ต๊ณ„ํฌํ„ธ(KOSIS) ๋ฐ e-์ง€๋ฐฉ์ง€ํ‘œ ์‹œ์Šคํ…œ, ํ•œ๊ตญ๋ถ€๋™์‚ฐ์› ์ „๊ตญ์ฃผํƒ๊ฐ€๊ฒฉ๋™ํ–ฅ์กฐ์‚ฌ๋ฅผ ํ†ตํ•ด ์‹œยท๊ตฐยท๊ตฌ ์ง€์—ญ์ˆ˜์ค€์˜ ์ฃผ๊ฑฐ๋น„ ๋ณ€๋™ ๋ฐ ๊ฐ€๊ฒฉ์ง€์ˆ˜ ๊ด€๋ จ ํ•ญ๋ชฉ์ธ ์•„ํŒŒํŠธ ์ „์„ธ๊ฐ€๊ฒฉ์ง€์ˆ˜, ์•„ํŒŒํŠธ ์›”์„ธ๊ฐ€๊ฒฉ์ง€์ˆ˜, ์ง€๊ฐ€๋ณ€๋™๋ฅ , ์ฃผํƒ๋งค๋งค๊ฐ€๊ฒฉ๋ณ€๋™๋ฅ , 1์ธ๊ฐ€๊ตฌ๋น„์œจ, 1์ธ๊ฐ€๊ตฌ ์ฃผํƒ์†Œ์œ ๋น„์œจ, ์ฃผํƒ๋งค๋งค๊ฐ€๊ฒฉ์ง€์ˆ˜, ๋งค๋งค๊ฐ€ ๋Œ€๋น„ ์ „์„ธ๊ฐ€๊ฒฉ๋น„์œจ์„ ํ™œ์šฉํ–ˆ์œผ๋ฉฐ, ์ง€์—ญ์‚ฌํšŒ๊ฑด๊ฐ•์กฐ์‚ฌ์˜ ์šฐ์šธ์ฆ์„ ๋ณ„๋„๊ตฌ(PHQ-9)์˜ ์ ์ˆ˜์ดํ•ฉ ๊ณ„์‚ฐ์„ ํ†ตํ•ด 10์  ์ด์ƒ์ธ ๊ฒฝ์šฐ ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘ ํ•ด๋‹น์œผ๋กœ ํ•˜์—ฌ ์ข…์†๋ณ€์ˆ˜๋กœ ํ•˜์˜€๋‹ค. ์‹œยท๊ตฐยท๊ตฌ ๋‹จ์œ„ ์ง€์—ญ์ˆ˜์ค€ ๋ณ€์ˆ˜๊ฐ€ ์ธก์ • ๊ฐ€๋Šฅํ•œ 156๊ฐœ ์ง€์—ญ์—์„œ ์ข…์†๋ณ€์ˆ˜์ธ ์šฐ์šธ์ฆ์ƒ์œ ๋ณ‘์ด ์ธก์ •๊ฐ€๋Šฅํ•œ ์„ฑ์ธ 1์ธ๊ฐ€๊ตฌ 21,588๋ช…์„ ์—ฐ๊ตฌ๋Œ€์ƒ์œผ๋กœ ํ•˜์˜€๊ณ  ๋‹ค์ˆ˜์ค€ ๋กœ์ง€์Šคํ‹ฑ๋ถ„์„์„ ์ด์šฉํ•˜์—ฌ ๊ฐœ์ธ์ˆ˜์ค€๊ณผ ์ง€์—ญ์ˆ˜์ค€์„ ๋™์‹œ์— ๊ณ ๋ ค, ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์š”์ธ์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ ์ „์ฒด ์—ฐ๊ตฌ๋Œ€์ƒ์ž 21,588๋ช… ์ค‘ ๋‚จ์„ฑ์€ 8,358๋ช…์ด๊ณ  ์—ฌ์„ฑ์€ 13,230๋ช…์ด์—ˆ์œผ๋ฉฐ, ์—ฐ๋ น์€ 65์„ธ ์ด์ƒ์ด 9,737๋ช…(45.32%)๋กœ ๊ฐ€์žฅ ๋งŽ์•˜๊ณ , 19-35์„ธ๊ฐ€ 3,084๋ช…(14.35%)๋กœ ๊ฐ€์žฅ ์ ์—ˆ๋‹ค. PHQ-9์˜ ์ ์ˆ˜๊ฐ€ 10์ ์„ ๋„˜๋Š” ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘๊ตฐ์€ 1,366๋ช…์œผ๋กœ ์ „์ฒด ์—ฐ๊ตฌ๋Œ€์ƒ์ž ์ค‘ 6.33%์˜€๋‹ค. ๊ฐœ์ธ ๋ฐ ์ง€์—ญ์ˆ˜์ค€ ๋ณ€์ˆ˜ ๊ฐ„ ์ƒ๊ด€๋ถ„์„์„ ํ†ตํ•ด ์ƒ๊ด€์„ฑ์ด ์žˆ๋Š” ๋ณ€์ˆ˜๋ฅผ ํ™•์ธํ•˜์˜€๊ณ  ์ตœ์ข… 11๊ฐœ์˜ ๊ฐœ์ธ์ˆ˜์ค€ ๋ณ€์ˆ˜์™€ 7๊ฐœ์˜ ์ง€์—ญ์ˆ˜์ค€ ๋ณ€์ˆ˜๋ฅผ ํˆฌ์ž…ํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ธฐ์ดˆ๋ชจ๋ธ ๋ถ„์„ ๊ฒฐ๊ณผ 1์ธ ๊ฐ€๊ตฌ ์„ฑ์ธ์˜ ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์š”์ธ ์ค‘ ์ง€์—ญ์ˆ˜์ค€์—์„œ ์ฐจ์ง€ํ•˜๋Š” ์„ค๋ช…๋ ฅ์ด 6.41%์œผ๋กœ ๋‚˜ํƒ€๋‚˜ ๋‹ค์ˆ˜์ค€๋ถ„์„์ด ๊ฐ€๋Šฅํ•จ์„ ํ™•์ธํ•˜์˜€๊ณ , ์ด๋ฅผ ์ ์šฉํ•˜์—ฌ ๋‹ค์Œ๊ณผ ๊ฐ™์€ ๊ฒฐ๊ณผ๋ฅผ ๋„์ถœํ•˜์˜€๋‹ค. ๋ถ„์„์— ํฌํ•จ๋œ ๊ฐœ์ธ์ˆ˜์ค€ ์š”์ธ ์ค‘ ์„ฑ๋ณ„, ์—ฐ๋ น, ๊ธฐ์ดˆ์ƒํ™œ์ˆ˜๊ธ‰์ž ์—ฌ๋ถ€ ๋ฐ ์›”ํ‰๊ท ์†Œ๋“์ด ์œ ์˜ํ•œ ๋ณ€์ˆ˜๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ ๊ฑด๊ฐ•ํ–‰ํƒœํ•™์  ๋ณ€์ˆ˜๋กœ๋Š” ํ˜„์žฌ ํก์—ฐ์ƒํƒœ, ์ฃผ๊ด€์  ๊ฑด๊ฐ•์ƒํƒœ, ์ค‘๋“ฑ๋„ ์‹ ์ฒดํ™œ๋™ ์‹ค์ฒœ์—ฌ๋ถ€, ๋น„๋งŒ์œ ๋ณ‘๋ฅ  ๋“ฑ์ด ์œ ์˜ํ•œ ๋ณ€์ˆ˜๋กœ ๋‚˜ํƒ€๋‚ฌ์œผ๋ฉฐ ์ง€์—ญ์ˆ˜์ค€ ๋ณ€์ˆ˜์—์„œ๋Š” ์•„ํŒŒํŠธ ์ „์„ธ๊ฐ€๊ฒฉ์ง€์ˆ˜ ๋ฐ ์•„ํŒŒํŠธ ์›”์„ธ๊ฐ€๊ฒฉ์ง€์ˆ˜, ์ฃผํƒ๋งค๋งค๊ฐ€๊ฒฉ๋ณ€๋™๋ฅ ๊ณผ 1์ธ๊ฐ€๊ตฌ ์ฃผํƒ์†Œ์œ ๋น„์œจ์ด ์œ ์˜ํ•œ ๋ณ€์ˆ˜๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ์ฆ‰ ๋‹ค๋ฅธ ์กฐ๊ฑด์ด ์ผ์ •ํ•  ๋•Œ, ๋‚จ์„ฑ์— ๋น„ํ•ด ์—ฌ์„ฑ์ธ ๊ฒฝ์šฐ, ์ฒญ๋…„(19~35์„ธ)์ผ ๊ฒฝ์šฐ, ๊ธฐ์ดˆ์ƒํ™œ์ˆ˜๊ธ‰์ž์ผ ๊ฒฝ์šฐ ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘ ์˜ค์ฆˆ๋น„๊ฐ€ ๋†’์•˜์œผ๋ฉฐ ํ˜„์žฌ ๊ธฐ์ดˆ์ƒํ™œ์ˆ˜๊ธ‰์ž์ผ ๊ฒฝ์šฐ, ๊ฐ€๊ตฌ ์›”ํ‰๊ท  ์†Œ๋“์ด ๋‚ฎ์„์ˆ˜๋ก, ์ดํ˜ผยท์‚ฌ๋ณ„ยท๋ณ„๊ฑฐ ๋“ฑ ๋ฐฐ์šฐ์ž ์ƒ์‹ค ์ƒํƒœ์ผ์ˆ˜๋ก ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘ ์˜ค์ฆˆ๋น„๊ฐ€ ๋†’์•˜๋‹ค. ๊ฑด๊ฐ•ํ–‰ํƒœ ๊ด€๋ จ์š”์ธ์—์„œ๋Š” ๋งค์ผ ํก์—ฐํ•˜๋Š” ๊ฒฝ์šฐ, ์ค‘๋“ฑ๋„ ์ด์ƒ ์‹ ์ฒดํ™œ๋™์„ ์‹ค์ฒœํ•˜๋Š” ๊ตฐ์— ๋น„ํ•ด ๋น„์‹ค์ฒœํ•˜๋Š” ๊ฒฝ์šฐ, ๋˜ํ•œ ์ฃผ๊ด€์ ์œผ๋กœ ๋Š๋ผ๋Š” ๊ฑด๊ฐ•์ƒํƒœ๊ฐ€ ๋‚˜์ ์ˆ˜๋ก ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘ ์˜ค์ฆˆ๋น„๋Š” ๋งค์šฐ ๋†’์•˜๋‹ค. ์ง€์—ญ์ˆ˜์ค€ ๋ณ€์ˆ˜๋ฅผ ๊ณ ๋ คํ•œ ํฅ๋ฏธ๋กœ์šด ๊ฒฐ๊ณผ๋กœ ์•„ํŒŒํŠธ ์ „์„ธ๊ฐ€๊ฒฉ์ง€์ˆ˜๊ฐ€ ๋†’์•„์งˆ์ˆ˜๋ก ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘ ์˜ค์ฆˆ๋น„๋Š” ๋‚ฎ์•„์กŒ์œผ๋ฉฐ(0.97), ์›”์„ธ๊ฐ€๊ฒฉ์ง€์ˆ˜๊ฐ€ ์˜ฌ๋ผ๊ฐˆ์ˆ˜๋ก ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘ ์˜ค์ฆˆ๋น„๋Š” ๋†’์•„์ง€๋Š”(1.08) ๊ฒฝํ–ฅ์„ ๋ณด์˜€๋‹ค. ๊ฒฐ๋ก  ๋ณธ ์—ฐ๊ตฌ๋Š” ์ „๊ตญ์˜ ์„ฑ์ธ 1์ธ๊ฐ€๊ตฌ๋ฅผ ๋Œ€์ƒ์œผ๋กœ ๊ฐœ์ธ ๋ฐ ์‹œยท๊ตฐยท๊ตฌ ๋‹จ์œ„ ์ฃผ๊ฑฐ๋น„ ๊ด€๋ จ ์ง€์—ญ์ˆ˜์ค€ ๋ณ€์ˆ˜๋ฅผ ๊ณ ๋ คํ•˜์—ฌ ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์š”์ธ์„ ๋ถ„์„ํ•œ ์—ฐ๊ตฌ๋กœ, ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘์— ๋Œ€ํ•œ ๊ฐœ์ธ ๋ฐ ์ง€์—ญ์ˆ˜์ค€์˜ ์œ ์˜ํ•œ ์˜ํ–ฅ์š”์ธ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๋ณด๋‹ค ๋‹ค์–‘ํ•˜๊ณ  ๊ตฌ์ฒด์ ์ธ ์‹œยท๊ตฐยท๊ตฌ ๋‹จ์œ„ ์ง€์—ญ์ˆ˜์ค€ ๋ณ€์ˆ˜๋ฅผ ์ด์šฉํ•˜์—ฌ ์ง€์—ญ์ˆ˜์ค€ ์ฃผ๊ฑฐ๋น„ ๊ด€๋ จ ๋ณ€์ˆ˜์™€ ๊ฐœ์ธ์˜ ์šฐ์šธ์ฆ์ƒ ์œ ๋ณ‘ ํ˜น์€ ์ฃผ๊ด€์  ๊ฑด๊ฐ•์ƒํƒœ ๋“ฑ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ํŒŒ์•…ํ•  ์ˆ˜ ์žˆ๋Š” ๊ธฐ์ดˆ์ž๋ฃŒ๋กœ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค.open์„

    Development of functional prediction marker for SSRIs response capitalizing on platelets

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์•ฝํ•™๊ณผ, 2013. 2. ์ •์ง„ํ˜ธ.Serotonin์„ ํฌํ•จํ•œ ์‹ ๊ฒฝ์ „๋‹ฌ๋ฌผ์งˆ์˜ ์กฐ์ ˆ ์ด์ƒ์€ ์šฐ์šธ์ฆ ๋ฐœ์ƒ์˜ ์ฃผ์š” ์›์ธ ์ค‘ ํ•˜๋‚˜์ด๋‹ค. Selective serotonin reuptake inhibitor (SSRI)๋Š” ๋Œ€ํ‘œ์ ์ธ ํ•ญ์šฐ์šธ์ œ๋กœ, pre-synaptic neuron์˜ serotonin transporter (SERT) ์˜ ์ž‘์šฉ์„ ์ฐจ๋‹จํ•˜์—ฌ serotonin์˜ ์žฌํก์ˆ˜๋ฅผ ์–ต์ œ์‹œํ‚ด์œผ๋กœ์จ ์‹œ๋ƒ…์Šค์—์„œ serotonin์˜ ์–‘์„ ํŠน์ด์ ์œผ๋กœ ์ฆ๊ฐ€์‹œํ‚ค๋Š” ํšจ๊ณผ๋ฅผ ๊ฐ€์ง„๋‹ค. ํ•˜์ง€๋งŒ ์ผ๋ถ€ ํ™˜์ž์˜ ๊ฒฝ์šฐ SSRI ์•ฝ๋ฌผ ์น˜๋ฃŒ์— ์˜ํ•œ ์ž„์ƒ ์ฆ์ƒ ๊ฐœ์„ ์„ ๋ณด์ด์ง€ ์•Š๋Š” non-responder๋กœ ๋ณด๊ณ ๋˜๊ณ  ์žˆ์–ด, ์•ฝ๋ฌผ ์น˜๋ฃŒ ์ „ SSRI response๋ฅผ ์˜ˆ์ธกํ•˜๊ธฐ ์œ„ํ•œ ์ƒ์ฒด์ง€ํ‘œ ๊ฐœ๋ฐœ์˜ ์ค‘์š”์„ฑ์ด ๋Œ€๋‘๋˜๊ณ  ์žˆ๋‹ค. ํ•œํŽธ, ํ˜ˆ์†ŒํŒ์€ serotonin์˜ ์ €์žฅ, ๋ถ„๋น„ ๋ฐ ๊ฐ์ž‘ ๋“ฑ ์ฃผ์š” ์กฐ์ ˆ๊ณผ์ •์ด ์‹œ๋ƒ…์Šค์™€ ๋งค์šฐ ์œ ์‚ฌํ•˜๊ธฐ ๋•Œ๋ฌธ์— ์‹ ๊ฒฝ์„ธํฌ ์—ฐ๊ตฌ๋ฅผ ์œ„ํ•œ peripheral model๋กœ ์ฃผ๋ชฉ ๋ฐ›๊ณ  ์žˆ๋‹ค. ํŠนํžˆ ํ˜ˆ์†ŒํŒ์˜ SERT์™€ serotonin receptor (5-HT2AR) ๋Š” ์‹ ๊ฒฝ์„ธํฌ์— ๋ฐœํ˜„๋˜์–ด ์žˆ๋Š” ๊ฒƒ๊ณผ ์œ ์ „์ ์œผ๋กœ ์™„์ „ํžˆ ๋™์ผํ•œ ๊ฒƒ์œผ๋กœ ์•Œ๋ ค์ ธ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ํ˜ˆ์†ŒํŒ๊ณผ ์‹ ๊ฒฝ์„ธํฌ์˜ ์œ ์‚ฌ์„ฑ์— ์ฃผ๋ชฉํ•˜์—ฌ, ํ˜ˆ์†ŒํŒ์˜ ๋ฐ˜์‘์„ฑ๊ณผ ์šฐ์šธ์ฆ์˜ ๋ฐœํ˜„ ๋ฐ SSRI์— ์˜ํ•œ ์น˜๋ฃŒํšจ๊ณผ ์‚ฌ์ด์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•œ ์‹คํ—˜์„ ๊ณ„ํšํ•˜์˜€๋‹ค. ํ˜ˆ์†ŒํŒ์˜ ์ƒ๋ฆฌ์  ๊ธฐ๋Šฅ์„ ์ธก์ •ํ•˜๊ธฐ ์œ„ํ•ด, ์ •์ƒ์ธ ๋ฐ ์šฐ์šธ์ฆ ํ™˜์ž์˜ ํ˜ˆ์•ก์—์„œ Platelet rich plasma (PRP)๋ฅผ ๋ถ„๋ฆฌํ•˜์—ฌ agonist ๋ฐ SSRI ์— ๋Œ€ํ•œ ํ˜ˆ์†ŒํŒ์˜ ๋ฐ˜์‘์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค. Agonist๋กœ๋Š” neurotransmitter์ธ serotonin๊ณผ epinephrine์„ ์ด์šฉํ•˜์˜€๋‹ค. ์ •์ƒ์ธ์—์„œ Aggregation ๋ฐ˜์‘์— ๊ฐœ์ธ์ฐจ๊ฐ€ ์กด์žฌํ•จ์„ ํ™•์ธํ•˜์˜€๊ณ , SSRI (fluoxetine) ์ „์ฒ˜๋ฆฌ์— ์˜ํ•ด aggregation ๋ฐ˜์‘ ๋ณ€ํ™” ์ •๋„์—๋„ ๊ฐœ์ธ์ฐจ๊ฐ€ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ํ˜ˆ์†ŒํŒ์„ฑ์˜ ๊ฐœ์ธ์ฐจ๋Š” ์šฐ์šธ์ฆ ํ™˜์ž์˜ ํ˜ˆ์†ŒํŒ์„ ์ด์šฉํ•œ aggregation, P-selectin expression ๋ฐ GPโ…กb/โ…ขa activation ์‹คํ—˜์—์„œ๋„ ํ™•์ธ๋˜์—ˆ์œผ๋ฉฐ, SSRI(Escitalopram)์„ ์ „์ฒ˜๋ฆฌํ•œ ๊ฒฝ์šฐ ํ˜ˆ์†ŒํŒ ๋ฐ˜์‘์˜ ๋ณ€ํ™”์—๋„ ๊ฐœ์ธ์ฐจ๋ฅผ ํ™•์ธํ•˜์˜€๋‹ค. ์ด๋Ÿฌํ•œ ํ˜ˆ์†ŒํŒ ๋ฐ˜์‘์„ฑ๊ณผ SSRI ๋ณต์šฉ ์‹œ ์ž„์ƒ์ ์ธ ์šฐ์šธ์ฆ ์ฆ์ƒ ๊ฐœ์„  ์ •๋„๋ฅผ ๋น„๊ต ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ, ํ˜ˆ์†ŒํŒ ๋ฐ˜์‘์„ฑ ์ง€ํ‘œ ์ค‘ ์ผ๋ถ€๊ฐ€ HAM-D score ๋ณ€ํ™” ์ •๋„์™€ ์œ ์˜์ ์ธ ์—ฐ๊ด€์„ฑ์„ ๋‚˜ํƒ€๋‚ด์—ˆ๋‹ค. ์ด๋Š” ์šฐ์šธ์ฆ ํ™˜์ž์—์„œ SSRI ๋ฐ˜์‘์„ฑ์„ ๋ฏธ๋ฆฌ ์˜ˆ์ธก ํ•˜๊ธฐ ์œ„ํ•œ ์ƒ์ฒด์ง€ํ‘œ๋กœ ํ˜ˆ์†ŒํŒ์ด ๊ฐ€๋Šฅ์„ฑ์„ ๊ฐ€์ง์„ ์‹œ์‚ฌํ•˜๋ฉฐ, ํ–ฅํ›„ ํ˜ˆ์†ŒํŒ์˜ ์ƒ๋ฆฌ์  ๊ธฐ๋Šฅ์„ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•œ SSRI ๋ฐ˜์‘์„ฑ์˜ ์˜ˆ์ธก ์ง€ํ‘œ ๊ฐœ๋ฐœ ๊ฐ€๋Šฅ์„ฑ์„ ํ™•์ธํ•˜์˜€๋‹ค.์š” ์•ฝ (๊ตญ๋ฌธ์ดˆ๋ก) -------------------------------โ…ฐ ๋ชฉ ์ฐจ -----------------------------------------โ…ฒ List of Figures ---------------------------------โ…ณ List of Abbreviations ---------------------------โ…ด ์„œ ๋ก  ------------------------------------------1 ์‹ค ํ—˜ ๋ฐฉ ๋ฒ• -------------------------------------5 ์‹œ์•ฝ ๋ฐ antibodies ------------------------------5 ์ •์ƒ์ธ ํ˜ˆ์†ŒํŒ์˜ ๋ฐ˜์‘์„ฑ ํ™•์ธ ---------------------5 Human platelet rich plasma ์˜ ๋ถ„๋ฆฌ --------------5 ํ˜ˆ์†ŒํŒ Aggregation ์ธก์ • -------------------------6 ์šฐ์šธ์ฆ ํ™˜์ž ํ˜ˆ์†ŒํŒ์˜ ๋ฐ˜์‘์„ฑ ํ™•์ธ -----------------6 Subject -----------------------------------------6 Protocol ----------------------------------------7 ์šฐ์šธ์ฆ ํ™˜์ž์˜ PRP ๋ถ„๋ฆฌ --------------------------7 ํ˜ˆ์†ŒํŒ์˜ ์ „์ฒ˜๋ฆฌ ---------------------------------8 ํ˜ˆ์†ŒํŒ Aggregation ์ธก์ • -------------------------8 P-selectin ๋ฐœํ˜„ ๋ฐ GPโ…กb/โ…ขa ํ™œ์„ฑํ™” ์ธก์ • --------10 ์ž๋ฃŒ ๋ถ„์„ ๋ฐ ํ†ต๊ณ„ ์ฒ˜๋ฆฌ --------------------------10 ์‹ค ํ—˜ ๊ฒฐ ๊ณผ -------------------------------------12 ๊ณ  ์ฐฐ ------------------------------------------31 ์ฐธ ๊ณ  ๋ฌธ ํ—Œ -------------------------------------35 Abstract ---------------------------------------40Maste
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