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¹Ì±¹ ¸®ÇÏÀ̴롤º¥Æ²¸®´ë °øµ¿¿¬±¸ÆÀ, ½Ä¼ö ¼Ó ³³ ³ëÃâ°ú ÅÂ¾Æ °Ç°­ °á°ú »çÀÌÀÇ ¿¬°ü¼º ÃÖÃÊ È®ÀÎ

¡º°Ç°­°æÁ¦ÇÐÀú³Î¡» ÃÖ½ÅÈ£¿¡ ¡®½Ä¼ö ¹× Ãâ»ý °á°úÀÇ ³³ : µÎ °³ÀÇ Á¤¼öÀå À̾߱⡯ ¿¬±¸³í¹® ¹ßÇ¥



¹Ì±¹ Ææ½Ç¹Ù´Ï¾ÆÁÖ¿¡ ¼ÒÀçÇÑ ¸®ÇÏÀÌ´ëÇаú ¸Å»çÃß¼¼Ã÷ÁÖ ¿ù¼¶¿¡ ¼ÒÀçÇÑ º¥Æ²¸®´ëÇÐÀÇ º¸°Ç°æÁ¦ÇÐ ¿¬±¸ÁøÀº ¹° ¼ÓÀÇ ³³(Lead ; Pb)°ú ºÒ¸®ÇÑ ÅÂ¾Æ °Ç°­ °á°ú »çÀÌÀÇ Àΰú °ü°è¸¦ È®ÀÎÇÑ Ã¹ ¿¬±¸°á°ú¸¦ ¹ßÇ¥Çß´Ù.

¹Ì±¹ Ææ½Ç¹Ù´Ï¾ÆÁÖ¿¡ ¼ÒÀçÇÑ ¸®ÇÏÀÌ´ëÇаú ¸Å»çÃß¼¼Ã÷ÁÖ ¿ù¼¶¿¡ ¼ÒÀçÇÑ º¥Æ²¸®´ëÇÐÀÇ º¸°Ç°æÁ¦ÇÐ ¿¬±¸ÁøÀº ¹° ¼ÓÀÇ ³³(Lead ; Pb)°ú ºÒ¸®ÇÑ ÅÂ¾Æ °Ç°­ °á°ú »çÀÌÀÇ Àΰú °ü°è¸¦ È®ÀÎÇÑ Ã¹ ¿¬±¸°á°ú¸¦ ¹ßÇ¥Çß´Ù.

 

¸®ÇÏÀÌ´ëÇÐ(Lehigh University)°ú º¥Æ²¸®´ëÇÐ(Bentley University)ÀÇ ¿¬±¸¿øÀº ¹°ÀÇ ³³°ú ÀúüÁß ¹× Á¶»ê°ú °°Àº ºÒ¸®ÇÑ ÅÂ¾Æ °Ç°­ °á°ú »çÀÌÀÇ ¿¬°ü¼ºÀ» È®ÀÎÇÑ ÃÖÃÊÀÇ ¿¬±¸º¸°í¼­¸¦ ÃÖ±Ù ¹ßÇ¥Çß´Ù.


¹Ì±¹ Ææ½Ç¹Ù´Ï¾ÆÁÖ º£µé·¹Çð¿¡ ¼ÒÀçÇÑ ¸®ÇÏÀÌ´ëÇаú ¸Å»çÃß¼¼Ã÷ÁÖ ¿ù¼¶¿¡ ¼ÒÀçÇÑ º¥Æ²¸®´ëÇÐÀÇ º¸°Ç°æÁ¦ÇÐ(health economics) ¿¬±¸ÁøÀº ¹° ¼ÓÀÇ ³³(Lead ; Pb)°ú ºÒ¸®ÇÑ ÅÂ¾Æ °Ç°­ °á°ú »çÀÌÀÇ Àΰú°ü°è¸¦ È®ÀÎÇÑ Ã¹ ¿¬±¸°á°ú¸¦ ¹ßÇ¥Çß´Ù. ¸¹Àº ¿¬±¸°¡ ³³ ³ëÃâ°ú °Ç°­ »çÀÌÀÇ »ó°ü °ü°è¸¦ ¹ß°ßÇßÁö¸¸, Áö±Ý±îÁö ¹®Çå¿¡¼­ Àΰú °ü°è°¡ ºÎÁ·Çß´Ù.


ÀÌ ¿¬±¸´Â ÃÖ±Ù ¡º°Ç°­°æÁ¦ÇÐÀú³Î(Journal of Health Economics)¡»¿¡ ¡®½Ä¼ö ¹× Ãâ»ý °á°úÀÇ ³³ : µÎ °³ÀÇ Á¤¼öÀå À̾߱â(article titled: Lead in Drinking Water and Birth Outcomes: A Tale of Two Water Treatment Plants)¡¯¶ó´Â Á¦¸ñÀÇ ±â»ç·Î ½Ç·È´Ù.


¸®ÇÏÀÌ´ëÇÐÀÇ °æÁ¦ÇÐ ±³¼öÀÎ ¾ç¹«Àú(Muzhe Yang)°ú ¹êƲ¸®´ëÇÐÀÇ ´Ù¹ß M. µ¥À̺ê(Dhaval M. Dave) ±³¼ö´Â ¿ÀÇÏÀÌ¿ÀÁÖ ´º¾îÅ©½Ã(City of Newark)¿¡ °ÅÁÖÇÏ´Â ÀÓ»êºÎÀÇ Á¤È®ÇÑ Áý ÁÖ¼Ò¿¡ ´ëÇÑ µ¥ÀÌÅÍ¿Í µÎ °³ÀÇ Á¤¼öÀåÀÌ ¼­ºñ½ºÇÏ´Â µµ½Ã ³»ÀÇ °ø°£ °æ°è ±¸ºÐ Á¤º¸¸¦ »ç¿ëÇß´Ù.


±×µéÀÇ ¿¬±¸´Â žÆÀÇ °Ç°­¿¡ ´ëÇÑ ÅÂ¾Æ ³³(Pb) ³ëÃâÀÇ Àΰú °ü°è¸¦ È®ÀÎÇϱâ À§ÇØ ÇÑ Ç÷£Æ®ÀÇ ¼­ºñ½º Áö¿ªÀÇ ½Ä¼ö·Î ħÃâµÇ´Â ¿øÀÎÀÌ µÈ ¹°ÀÇ pH(¼ö¼ÒÀ̿³óµµ) ¼öÁØÀÇ ¿ÜÀμº(exogenous) ¶Ç´Â ¿ÜºÎ º¯È­(external change)¸¦ ÀÌ¿ëÇß´Ù.


¾ç¹«Àú(Muzhe Yang) ±³¼ö¿Í ¿¬±¸ÆÀµéÀº °Ç°­¿¡ ÁÁÁö ¾ÊÀº ¿µÇâÀ» ³¢Ä£´Ù´Â °­·ÂÇÑ Áõ°Å¸¦ ¹ß°ßÇß´Ù. °á°ú Áß, ÅÂ¾Æ ³³ ³ëÃâÀº ÀúüÁß Ãâ»ý È®·üÀ» 18% Áõ°¡Çß°í, Á¶»ê È®·üÀº 19% Áõ°¡Çß´Ù´Â °ÍÀÌ´Ù.


¾ç ±³¼ö´Â ¡°Æ¯È÷ ³ëÈÄÈ­µÈ ±â¹Ý½Ã¼³ÀÇ ÀϺηΠ»ç¿ëµÇ°í ÀÖ´Â ³³ ¼öµµ°üÀÇ »ó´ç¼ö¿Í ³³ Àú°¨ °³ÀÔÀÇ ºñ¿ë ÆíÀÍ ¹ÌÀûºÐÇп¡ ºñÃß¾î º¼ ¶§ ÀÌ ¿¬±¸ °á°ú´Â Áß¿äÇÑ Á¤Ã¥Àû Àǹ̸¦ °®´Â´Ù¡±°í °­Á¶Çß´Ù.


¾ç ±³¼ö´Â ¡°´º¾îÅ©½ÃÀÇ À§±â°¡ ´Ü¼ö°¡ ¾Æ´Ï¶ó ±¹°¡ÀÇ ³ëÈÄÈ­ µÈ ¹° ±â¹Ý ½Ã¼³À» »ó¡ÇÑ´Ù¡±°í ÁöÀûÇÑ´Ù.


¹Ì±¹ ¼Ò¾Æ°úÇÐȸ(American Academy of Pediatrics)¿¡ µû¸£¸é, ¾î¸°À̸¦ À§ÇØ È®ÀÎµÈ ³³ ³ëÃâ¿¡ ´ëÇÑ ¾ÈÀüÇÑ ±âÁØÀº ¾ø´Ù. ³³Àº ¹Ýº¹ÀûÀÎ ³ëÃâÀ» ÅëÇØ ÀÎü¿¡ ½Ã°£ÀÌ Áö³²¿¡ µû¶ó ¼öÁýµÇ¸ç Ä®½·(calcium ; Ca)°ú ÇÔ²² »À¿¡ ÀúÀåµÈ´Ù.

 

¸®ÇÏÀÌ´ëÇÐÀÇ ¾ç¹«Àú(Muzhe Yang) ±³¼ö´Â ¹° ¼ÓÀÇ ³³ÀÌ ÀÓ»êºÎ ÅÂ¾Æ °Ç°­¿¡ ÁÁÁö ¾ÊÀº ¿µÇâÀ» ³¢Ä£´Ù´Â °­·ÂÇÑ Áõ°Å¸¦ ¹ß°ßÇß´Ù.   [»çÁøÃâó(Photo source) = ¸®ÇÏÀÌ´ëÇÐ(Lehigh University)]
¸®ÇÏÀÌ´ëÇÐÀÇ ¾ç¹«Àú(Muzhe Yang) ±³¼ö´Â ¹° ¼ÓÀÇ ³³ÀÌ ÀÓ»êºÎ ÅÂ¾Æ °Ç°­¿¡ ÁÁÁö ¾ÊÀº ¿µÇâÀ» ³¢Ä£´Ù´Â °­·ÂÇÑ Áõ°Å¸¦ ¹ß°ßÇß´Ù. [»çÁøÃâó(Photo source) = ¸®ÇÏÀÌ´ëÇÐ(Lehigh University)] 

Àڱÿ¡¼­´Â ÀӽŠÁß¿¡ ¸ðüÀÇ »À¿¡ ÀÖ´Â ³³ÀÌ µ¿¿øµÇ¾î žÆÀÇ »À Çü¼ºÀ» µ½±â À§ÇØ Ä®½· ´ëü¹°·Î ¹æÃâµÉ ¼ö ÀÖ°í, ¸ðüÀÇ Ç÷¾×¿¡ ÀÖ´Â ³³µµ ŹÝÀ» °¡·ÎÁú·¯ žƸ¦ ³³Áßµ¶¿¡ ³ëÃâ½Ãų ¼ö Àֱ⠶§¹®¿¡ ƯÈ÷ ¿ì·ÁµÈ´Ù. žƱâÀÇ ³³ ³ëÃâÀº ¼Õ»óµÈ ½Å°æ ¹ß´Þ°ú °ü·ÃµÇ¾î ³ªÁß¿¡ ¾ÆÀ̵éÀ» ÀÎÁö Àå¾ÖÀÇ À§Çè¿¡ óÇÏ°Ô ÇÑ´Ù.


¹Ì ȯ°æº¸È£Ã»(EPA)Àº ½Ä¼ö°¡ ¼ºÀÎÀÇ ÃÑ ³³ ³ëÃâ·®ÀÇ 2% ÀÌ»óÀ» Â÷ÁöÇÏ°í À¯¾ÆÀÇ °æ¿ì 40¡­60%¸¦ Â÷ÁöÇÒ ¼ö ÀÖ´Ù°í ÃßÁ¤ÇÑ´Ù.


¾ç¹«Àú(Muzhe Yang) ±³¼ö¿Í ´Ù¹ß M. µ¥À̺ê(Dhaval M. Dave) ±³¼ö´Â ÀÚ½ÅÀÇ ¿¬±¸³í¹®À» ¼Ò°³Çϸ鼭 ´ÙÀ½°ú °°ÀÌ ¼­¼úÇß´Ù. 


¡°À½¿ë¼ö ¿À¿°Àº ȯ°æ¿À¿°¿¡ ´ëÇÑ Å¾Ʊ⠳ëÃâÀÇ Á¡Á¡ ´õ Áß¿äÇÏ°í ±¤¹üÀ§ÇÑ ¿øÀÎÀÌ µÇ°í ÀÖ´Ù. 2018³â¿¡¼­ 2020³â »çÀÌ¿¡ °ÅÀÇ 3õ¸¸ ¸íÀÇ »ç¶÷µéÀÌ EPAÀÇ ³³ ¹× ±¸¸® ±ÔÄ¢À» À§¹Ý ÇÑ Áö¿ª ¼ö°è¿¡¼­ ½Ä¼ö¸¦ ¼·ÃëÇßÀ¸¸ç, ÀÌ´Â ½Ä¼ö¿¡¼­ ÀÌ·¯ÇÑ ±Ý¼ÓÀÇ ÃÖ´ë ½ÃÇà °¡´ÉÇÑ ¼öÁØÀ» ¼³Á¤Çß´Ù.¡±


¾ç ±³¼ö´Â ¡°³³ ¼öµµ°ü ±³Ã¼¸¦ À§ÇÑ 150¾ï ´Þ·¯(19Á¶8õ750¾ï ¿ø)ÀÇ Àç¿øÀÌ Æ÷ÇÔµÈ ÀÇȸ Åë°ú ÀÎÇÁ¶ó ¹ý¾È¿¡¼­ ¹®Á¦ÀÇ ½Ã±Þ¼ºÀÌ ÃÖÁ¾ÀûÀ¸·Î ÀÎÁ¤µÅ ±â»Ú´Ù¡±°í ¸»Çß´Ù.


 

°á·Ð(Conclusion)


¾ç¹«Àú(Muzhe Yang) ±³¼ö¿Í ´Ù¹ß M. µ¥À̺ê(Dhaval M. Dave) ±³¼ö´Â ÀÚ½ÅÀÇ ¿¬±¸³í¹®ÀÎ ¡®½Ä¼ö ¹× Ãâ»ý °á°úÀÇ ³³ : µÎ °³ÀÇ Á¤¼öÀå À̾߱â(article titled: Lead in Drinking Water and Birth Outcomes: A Tale of Two Water Treatment Plants)¡¯°á·ÐÀ» ´ÙÀ½°ú °°ÀÌ ³»·È´Ù. 


¿ì¸®´Â ´º¾îÅ©½Ã¿¡¼­ ³³ À§±âÀÇ ¿µÇâ¿¡ ´ëÇÑ Ã¹ ¹ø° ¿¬±¸¸¦ Á¦°øÇϸç, ¼öµ¾¹°À» ÅëÇØ ³³ÀÇ ÅÂ¾Æ ³ëÃâÀÌ Ãâ»ý °á°ú¿¡ ¾î¶»°Ô ¿µÇâÀ» ¹ÌÄ¡´ÂÁö ¾Ë·ÁÁØ´Ù. ÀÌ·¯ÇÑ È¿°ú¸¦ Á¤·®È­ÇÏ´Â °ÍÀº ¿©·¯ °¡Áö ÀÌÀ¯·Î Áß¿äÇÏ´Ù.

 

ÀÌ ¿¬±¸º¸°í¼­ÀÇ °øµ¿ÀúÀÚÀÎ º¥Æ²¸®´ëÇÐÀÇÀÇ ´Ù¹ß M. µ¥À̺ê(Dhaval M. Dave) ±³¼ö´Â žÆÀÇ °Ç°­¿¡ ´ëÇÑ ÅÂ¾Æ ³³(Pb) ³ëÃâÀÇ Àΰú °ü°è¸¦ È®ÀÎÇϱâ À§ÇØ ÇÑ Ç÷£Æ®ÀÇ ¼­ºñ½º Áö¿ªÀÇ ½Ä¼ö·Î ħÃâµÇ´Â ¿øÀÎÀÌ µÈ ¹°ÀÇ pH(¼ö¼ÒÀ̿³óµµ) ¼öÁØÀÇ ¿ÜÀÎÀû(exogenous) ¶Ç´Â ¿ÜºÎ º¯È­(external change)¸¦ ÀÌ¿ëÇß´Ù. [»çÁøÃâó(Photo source) = º¥Æ²¸®´ëÇÐ(Bentley University)]
ÀÌ ¿¬±¸º¸°í¼­ÀÇ °øµ¿ÀúÀÚÀÎ º¥Æ²¸®´ëÇÐÀÇÀÇ ´Ù¹ß M. µ¥À̺ê(Dhaval M. Dave) ±³¼ö´Â žÆÀÇ °Ç°­¿¡ ´ëÇÑ ÅÂ¾Æ ³³(Pb) ³ëÃâÀÇ Àΰú °ü°è¸¦ È®ÀÎÇϱâ À§ÇØ ÇÑ Ç÷£Æ®ÀÇ ¼­ºñ½º Áö¿ªÀÇ ½Ä¼ö·Î ħÃâµÇ´Â ¿øÀÎÀÌ µÈ ¹°ÀÇ pH(¼ö¼ÒÀ̿³óµµ) ¼öÁØÀÇ ¿ÜÀÎÀû(exogenous) ¶Ç´Â ¿ÜºÎ º¯È­(external change)¸¦ ÀÌ¿ëÇß´Ù. [»çÁøÃâó(Photo source) = º¥Æ²¸®´ëÇÐ(Bentley University)]

 Ã¹Â°, ´º¾îÅ©½ÃÀÇ À§±â´Â ´Ü¼ö°¡ ¾Æ´Ï¶ó ¹Ì±¹ÀÇ ¸¹Àº ´Ù¸¥ µµ½ÃµéÀÌ ¹° °ø±Þ¿¡¼­ ³³ ¿À¿°¿¡ Á÷¸éÇÔ¿¡ µû¶ó ±¹°¡ÀÇ ³ëÈÄÈ­µÈ ¹° ÀÎÇÁ¶ó¸¦ »ó¡ÇÑ´Ù. º¼Æ¼¸ð¾î, ½ÃÄ«°í, µðÆ®·ÎÀÌÆ®, ¹Ð¿öÅ°, ´º¿å, ÇÇÃ÷¹ö±× ¹× ¿ö½ÌÅÏ D.C.ÀÇ ¼öµ¾¹°¿¡¼­ ³ôÀº ³³ ³óµµ°¡ ¹ß°ßµÇ¾úÀ¸¸ç, 2018 ³â°ú 2020³â »çÀÌ¿¡ °ÅÀÇ 3õ¸¸ ¸íÀÇ »ç¶÷µéÀÌ EPAÀÇ ³³ ¹× ±¸¸® ±ÔÄ¢(Fedinick, 2021; Mulvihill, 2021)À» À§¹Ý ÇÑ Áö¿ª ¼ö°è¿¡¼­ ½Ä¼ö¸¦ ¹Þ¾Ò´Ù.


¹Ì±¹Åä¸ñÇÐȸ(American Society of Civil Engineers)´Â 2017³â º¸°í¼­¿¡¼­ ¹Ì±¹ÀÇ ½Ä¼ö ½Ã½ºÅÛÀ» Dµî±ÞÀ¸·Î Æò°¡Çϸç, ³ëÈÄÈ­µÈ ÆÄÀÌÇÁ¿Í ³³°ú °°Àº ¿À¿°¹°Áú¿¡ ´ëÇÑ »õ·Î¿î ¹®Á¦¸¦ °­Á¶Çß´Ù.


¹Ì±¹ ¼öµµ ½Ã½ºÅÛÀÇ ¸ðµç ³³ ÆÄÀÌÇÁ¸¦ ±³Ã¼ÇØ¾ß ÇÏ´Â ±ä±Þ¼ºÀº 2021³â 11¿ù ¹Ì±¹ ÀÇȸ°¡ Á¦Á¤ÇÑ ¡¸ÀÎÇÁ¶ó ÅõÀÚ ¹× °í¿ë¹ý¡¹¿¡¼­ 150¾ï ´Þ·¯ÀÇ ³³ ¼öµµ°ü ±³Ã¼ ÀÚ±ÝÀ» Æ÷ÇÔÇÏ¿© ¸¶Ä§³» ÀÎÁ¤µÇ¾ú´Ù.


µÑ°, ³³ÀÇ °Ç°­ ¿µÇâ¿¡ ´ëÇÑ ¿ì¸®ÀÇ ¸¹Àº ÀÌÇØ´Â Ç÷Áß ³³ ³óµµ¿Í °Ç°­ °á°ú »çÀÌÀÇ ÀáÀçÀûÀÎ ³»Àμº ¿¬°ü¼º¿¡¼­ ºñ·ÔµÈ´Ù. ´º¾îÅ©½ÃÀÇ ¹° À§±â´Â ³³ ³ëÃâÀÇ º¯µ¿¿¡ ´ëÇÑ ±×·²µíÇÏ°Ô ¿Ü»ýÀûÀÎ ¿øÀÎÀ» Á¦°øÇÏ¿© ÅÂ¾Æ °Ç°­¿¡ ´ëÇÑ ÅÂ¾Æ ³ëÃâÀÇ ÀΰúÀû ¿µÇâÀ» ½Äº°ÇÒ ¼ö ÀÖ°Ô ÇØÁØ´Ù. ÀÌ´Â ¹° ½Ã½ºÅÛÀÌ ½ÇÆÐÇÒ ¶§ ¸ðµç ä³Î(»ý¹°ÇÐÀû, ÇൿÀû)À» ÅëÇØ ÀÛµ¿Çϱ⠶§¹®¿¡ Àα¸ÀÇ Àü¹ÝÀûÀÎ ¿µÇâÀ» Æ÷ÂøÇϱ⠶§¹®¿¡ µÎµå·¯Áø´Ù.


¿ì¸®°¡ ÃßÁ¤ÇÑ È¿°ú´Â ³³ ³ëÃâ·Î ÀÎÇÑ °Ç°­ À§ÇèÀ» Á¦°ÅÇϱ⿡ ºÒÃæºÐÇÑ Çൿ ¹ÝÀÀÀÇ Á¸À縦 ¹Ý¿µÇϱ⠶§¹®¿¡ Áï°¢ÀûÀÎ Á¤Ã¥Àû °ü½ÉÀÌ´Ù. ¶ÇÇÑ Àα¸ÀÇ Ç÷Áß ³³ ³óµµ´Â Áö³­ 50³â µ¿¾È »ó´çÈ÷ °¨¼ÒÇß´Ù. µû¶ó¼­ ¿ì¸®ÀÇ ¿¬±¸´Â ÇöÀçÀÇ ³·Àº ±âÁؼ±¿¡ ºñÇØ ³ëÃâ Áõ°¡ÀÇ ¿µÇâÀ» Æ÷ÂøÇß´Ù.


¼Â°, ¸¹Àº °øÁߺ¸°Ç ¿ËÈ£·ÐÀÚµé°ú ¼öµµ ½Ã½ºÅÛ Àü¹®°¡µéÀº ÀÌ¹Ì ¼º°øÀûÀÎ ´ëü ÇÁ·Î±×·¥À» ½ÃÇà ÇÑ ÀϺΠÁö¿ª »çȸ¿Í ´Ù¸¥ µµ½ÃµéÀÌ ±×·¸°Ô ÇÒ ¼ö ÀÖ´Â °èȹÀ» °³¹ßÇϸ鼭 ±¹°¡ÀÇ ¾à 600¸¸¡­1õ¸¸ °³ÀÇ ³³ ¼­ºñ½º ¶óÀÎÀ» ¿ÏÀüÈ÷ ´ëü ÇÒ °ÍÀ» Ã˱¸Çß´Ù.


ÀÌ·¯ÇÑ °ø°ø ÅõÀÚÀÇ ºñ¿ë ¿µÇâ¿¡ ´ëÇÑ Æ÷°ýÀûÀÎ Æò°¡´Â ³³ ³ëÃâÀÇ °øÁß º¸°Ç ¿µÇâ¿¡ ´ëÇÑ ÃßÁ¤À» ÇÊ¿ä·Î ÇÑ´Ù. ¿ì¸®´Â ´º¾îÅ©ÀÇ ³³ ¿À¿°¿¡ ´ëÇÑ Àڱà ³ëÃâÀÇ Áõ°¡°¡ LBW ¶Ç´Â Á¶»êÀ¸·Î ž À¯¾ÆÀÇ À¯º´·üÀ» À¯ÀÇÇÏ°Ô Áõ°¡ ½ÃÄ×´Ù´Â °­·ÂÇÏ°í ÀÏ°üµÈ Áõ°Å¸¦ ¹ß°ßÇß´Ù.


ÀÌ·¯ÇÑ È¿°ú°¡ Ãâ»ýÀ¸·ÎÀÇ ¼±Åÿ¡ ÀÇÇØ Á¿ìµÈ´Ù´Â Áõ°Å´Â °ÅÀÇ ¾ø´Ù. ¿ì¸®ÀÇ ÃßÁ¤Ä¡´Â LBWÀÇ °¡´É¼ºÀÌ ¾à 1.5% Æ÷ÀÎÆ®(¶Ç´Â 18%) Áõ°¡ÇÏ°í Á¶»ê °¡´É¼ºÀÌ ¾à 1.9% Æ÷ÀÎÆ®(¶Ç´Â 19%) Áõ°¡ÇÑ´Ù´Â °ÍÀ» ³ªÅ¸³½´Ù.


À̰͵éÀº ¼öµ¾¹°ÀÇ ³³ ³óµµ°¡ Áõ°¡ÇÑ Áö¿ª¿¡¼­ ÀӽŠÁß¿¡ °ÅÁÖÇÏ´Â ÀǵµÀûÀÎ Ä¡·á È¿°úÀÌ´Ù. ¿Ö³ÄÇÏ¸é ¿©±â¿¡ °ÅÁÖÇÏ´Â »ç¶÷µéÀº ³ôÀº ¼öÁØÀÇ ³³¿¡ ³ëÃâµÇ¾î Àֱ⠶§¹®ÀÌ´Ù. µµ½ÃÀÇ ÁÖ¿ä ¼­ºñ½º ¶óÀÎ ¸ñ·ÏÀÇ ÀϺηΠµµ½Ã ¼­ºñ½º ¶óÀÎÀÇ ¾à 61%°¡ ³³À¸·Î ±¸¼ºµÇ¾ú´Ù.


ÀÌ ³ëÃâ È®·ü¿¡ ÀÇÇÑ Ã³¸® È¿°ú¸¦ ºÎÇ®¸®´Â °ÍÀº ³³ ³ëÃâ ¼öÁØÀÌ ³ôÀ»¼ö·Ï È¿°ú Å©±â°¡ 2.5 ¡­3.1 % Æ÷ÀÎÆ®ÀÓÀ» ÀǹÌÇÑ´Ù. ¿ì¸®ÀÇ ÃßÁ¤¿¡ µû¸£¸é ´º¾îÅ©½ÃÀÇ ¼öÁß À§±â·Î ÀÎÇØ ÁÖ¾îÁø ÇØ¿¡ Ãâ»ê½Ã ÀúüÁß¾Æ(LBW ; low birthweight infant)°¡ ¾à 27¿¡¼­ 49LBW ¶Ç´Â Á¶»ê¾Æ°¡ Áõ°¡ÇÑ °ÍÀ¸·Î ÃßÁ¤µÈ´Ù.


2019³â 3¿ù, ´º¾îÅ©½Ã´Â ÁÖÅà ¼ÒÀ¯ÀÚ¿¡°Ô ¹«·á·Î ¼öµµ ½Ã½ºÅÛÀÇ ¸ðµç µµ½ÃÀÇ ³³ ¼­ºñ½º ¶óÀÎÀ» Á¦°ÅÇÏ°í ±³Ã¼ÇÏ´Â ÇÁ·Î±×·¥À» ½ÃÀÛÇßÀ¸¸ç, ¿¹»ó ºñ¿ëÀº 9õ¸¸ ´Þ·¯¿¡¼­ 1¾ï8õ¸¸ ´Þ·¯ÀÌ´Ù. Á¶»ê¾ÆÀÇ Æò»ý »çȸ¡¤°æÁ¦Àû ºÎ´ãÀÌ ¾à  6¸¸7õ532´Þ·¯(Institute of Medicine, 2007)·Î ÃßÁ¤µÊ¿¡ µû¶ó ´º¾îÅ©½ÃÀÇ ³³ À§±âÀÇ ¿¬°£ »çȸ ºñ¿ëÀº ¸Å³â Áõ°¡µÈ ³³ ³ëÃâ°ú °ü·ÃµÈ À¯¾Æ °Ç°­ ¾ÇÈ­·Î ÃßÁ¤µÇ´Â 182¾ï 3õ100¸¸ ´Þ·¯¿¡ À̸¥´Ù.


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ÀÌ ¿¬±¸º¸°í¼­ÀÇ ¿ø¹®Àºw27996.pdf (nber.org)¸¦ ÂüÁ¶.


[¿ø¹®º¸±â]


 Study: Lead in Water Causes Adverse Fetal Health Outcomes



Researchers from Lehigh and Bentley universities publish the first study that confirms a link between lead in water and adverse fetal health outcomes such as low birth weights and preterm births.


Lehigh University and Bentley University health economics researchers have published the first study to confirm a causal relationship between lead in water and adverse fetal health outcomes. Although many studies have found a correlation between lead exposure and health, a causal link had been lacking in the literature?until now. 


The study has recently been published in the Journal of Health Economics in an article titled: Lead in Drinking Water and Birth Outcomes: A Tale of Two Water Treatment Plants.


The researchers, Muzhe Yang, professor of economics at Lehigh, and Dhaval M. Dave of Bentley University, used data on the exact home addresses of pregnant women living in the City of Newark together with information on the spatial boundary separating areas within the city serviced by two water treatment plants. 


Their study exploits an exogenous, or external, change in the water¡¯s pH level that caused lead to leach into the drinking water of one plant¡¯s service area, but not the other¡¯s, to identify the causal effect of prenatal lead exposure on fetal health.


Yang and his colleague found robust evidence of adverse health impacts. Among the findings: prenatal lead exposure increased the chance of low birth weight by 18% and increased the probability of preterm birth by 19%.  


¡°These findings have important policy implications,¡± says Yang, ¡°especially in light of the substantial number of lead water pipes that remain in use as part of the aging infrastructure and the cost-benefit calculus of lead abatement interventions.¡±


Yang notes that the crisis in Newark is not singular, but rather emblematic of the nation¡¯s aging water infrastructure.


According to the American Academy of Pediatrics, there is no safe threshold for lead exposure that has been identified for children. Lead collects over time in the human body through repeated exposure and is stored in the bones alongside calcium. 


In utero exposure is of particular concern as lead in the mother¡¯s bones can be mobilized during pregnancy and released as a calcium substitute to aid in the formation of the bones of the fetus, and lead in a mother¡¯s blood can also cross the placenta, exposing the fetus to lead poisoning. Prenatal lead exposure has been associated with impaired neural development putting children at risk for cognitive impairment later.


The Environmental Protection Agency (EPA) estimates that drinking water may account for more than 20 percent of total lead exposure for adults and 40 to 60 percent for infants. 


In the introduction to their paper, Yang and Dave write: ¡°Drinking water contamination is becoming an increasingly important and widespread source of prenatal exposure to environmental pollution. Between 2018 and 2020, nearly 30 million people received their drinking water from community water systems that were in violation of the EPA¡¯s Lead and Copper Rule, which sets maximum enforceable levels of these metals in drinking water¡¦¡± 


¡°We are glad that the urgency of the problem was finally recognized in the infrastructure bill passed by the Congress that includes funding of $15 billion for lead pipe replacement,¡± said Yang.


Conclusion


We provide the first study of the effects of the lead crisis in Newark, informing how prenatalexposure to lead through tap water impacts birth outcomes. Quantifying these effects isimportant for several reasons.


First, the crisis in Newark is not singular, but rather em blematic of the nation¡¯s aging water infrastructure as many other cities in the U.S. face leadcontamination in their water supply.


High lead levels have been found in the tap water inBaltimore, Chicago, Detroit, Milwaukee, New York, Pittsburgh, and Washington D.C., andbetween 2018 and 2020 nearly 30 million people in the nation received their drinking waterfrom community water systems that were in violation of the EPA¡¯s Lead and Copper Rule(Fedinick, 2021; Mulvihill, 2021).


The American Society of Civil Engineers in its 2017 reportcard rated the nation¡¯s drinking water system a D grade, underscoring the aging pipes andemerging problems with contaminants such as lead.


The urgency of replacing all lead pipesin the U.S. water systems was finally recognized in the Infrastructure Investment and JobsAct enacted by the U.S. Congress in November 2021 that includes funding of $15 billion forlead pipe replacement.


Second, much of our understanding of the health effects of lead comes from potentiallyendogenous associations between blood lead levels and health outcomes. The water crisis in Newark provides a plausibly exogenous source of variation in lead exposure, allowing us toidentify a causal effect of prenatal exposure on fetal health?an effect that is salient becauseit captures the overall impact in the population, operating through all channels (biologicaland behavioral, including any avoidance behaviors) when water systems fail.


The effectwe estimated is also of immediate policy interest since our estimate reflects the presence ofbehavioral responses that are insufficient for eliminating the health risk due to lead exposure.Moreover, population blood lead levels have declined considerably over the past five decades.Our study therefore captures the effects of an increase in exposure relative to a current lowbaseline.


Third, many public health advocates and experts on water systems have called for fullreplacement of the nation¡¯s estimated 6 to 10 million lead service lines, with some communi ties already having implemented successful replacement programs and other cities developingplans to do so


A comprehensive evaluation of the cost implications of such public invest ments requires estimates of the public health impact of lead exposure.We find robust and consistent evidence that the increased in utero exposure to leadthrough water contamination in Newark significantly increased t


e prevalence of infantsbeing born with LBW or preterm.


There is little evidence to suggest that these effects aredriven by selection into births. Our estimates indicate an approximately 1.5 percentage-point(or 18 percent) increase in the likelihood of LBW, and an approximately 1.9 percentage-point(or 19 percent) increase in the likelihood of a preterm birth.


These are intention-to-treateffects of residing during pregnancy in areas with increased lead levels in tap water, since notevery resident here is being exposed to high levels of lead. As part of the city¡¯s lead serviceline inventory, approximately 61 percent of the city service lines were constructed of lead.


Inflating the treatment effects by this ¡°exposure¡± probability implies effect sizes between 2.5and 3.1 percentage points, with respect to higher levels of lead exposure. Our estimatesimply an increase of about 27 to 49 LBW or preterm births in a given year attributed to thelead-in-water crisis in Newark.


In March 2019, Newark commenced a program to remove and replace all of the city¡¯slead service lines in the water system at no cost to the homeowner, at a projected publiccost of $90?$180 million. With the lifetime societal economic burden of a preterm birthestimated to be approximately $67,532 (Institute of Medicine, 2007),  the annual societalcost of the lead crisis in Newark amounts to $1.82?$3.31 million from the estimated increasein worse infant health linked to the heightened lead exposure each year.


 Assuming adiscount rate for public policy of 2% based on the social rate of time preference (Councilof Economic Advisers, 2017), societal cost savings from averting this adverse fetal healthcould be between $91 and $166 million.


These calculations suggest that the benefits are roughly the same order of magnitude as the intervention costs, offsetting much, if not all, ofthe public sector cost of lead abatement through service line replacement.


That the public values such investments to improve the water system infrastructurein the nation is apparent from the considerable engagement in avoidance behaviors whencontaminant violations in water systems are disclosed to the public (Graff Zivin, Neidelland Schlenker, 2011).


According to McCarthy (2017), drinking water pollution worriesare also at their highest levels since 2001, with 63% of the public reporting that they areworried a great deal about this issue; concern is even higher among low-income individuals(75%) and non-whites (80%).


The cost-saving estimates we previously discussed are likelyto be lower-bound estimates given that the focus of this study is specifically on adversefetal health effects; lead exposure among children has also been found to independentlyand adversely impact their development, increasing anti-social and criminal behaviors andreducing achievement in school.


We qualify this discussion that since our estimates are derived from a city composed ofa population of lower socioeconomic status (SES) compared to the U.S. as a whole (or evenan average similarly-sized city), the effects may not necessarily generalize due to variationin media exposure, information processing, and mitigation behaviors.


However, Newark isemblematic of another pattern that speaks to the significance and external validity of ourestimates; low-income and high-minority communities have, in particular, been found to facedisproportionately higher pollutant exposures, and especially greater exposure to drinkingwater contamination, for various reasons (Schaider et al., 2019).


Thus, for communities thatare experiencing issues with lead-related water contamination, which tend to be low-SESand minority-prevalent communities, the estimates from this study are highly salient and would have greater external validity.


ÀÌ ¿¬±¸º¸°í¼­ÀÇ ¿ø¹®Àº w27996.pdf (nber.org)¸¦ ÂüÁ¶.


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