Table 4.
SL No | Author Details | n | Study Population | The Method Used to Measure Attrition | r Value | Clinical Significance |
---|---|---|---|---|---|---|
1 | Miles (1962)15 | n=190 | Anglo-saxon settlement (skeletal remains) | Miles Method | Not applicable | The ratio between rates of wear of 1st, 2nd and 3rd molars is more or less constant despite the nature of the diet in different populations. |
2 | Akpata ES (1975)16 | n = 352 | Nigeria (Africa) | Murphy’s classification of attrition | r=0.928 −0.979 for 2nd and 1st molar | Attrition is an index of wear and masticatory activity. |
3 | Nowell (1979)12 | n =268 | Tepe Hissar, Iran | Miles method |
r = 0.87 93% estimated within 5 years |
Provided evidence of reliability and validity of Miles method. Not possible to derive reliable demographic details from this sample. |
4 | Brothwell (1981)17,18 | Not applicable | British Neolithic to Mediaeval groups | Not applicable | Not applicable | Distinguishes young skulls from those over 40 years of age. Not useful in identifying those with advanced age. |
5 | Kieser et al (1983)13 | n=202 | Paraguay stone casts of living individuals | Miles method | r = 0.95 | Found Miles method to be reliable. |
6 | Lovejoy CO (1985)19 | n =332 | Libben population (USA) | Murphy’s classification |
r = 0.93 ᵨ = 0.96 |
Even attrition rates. Compared to skeletal indicators, attrition is the single best method. Higher wear rates in females. |
7 | Hongwei and Jingtao (1989)20 | n=24,640 (Teeth) 880 -individuals | Chinese (urban and rural areas) | Takei 1970 |
r=0.61−0.83 5-year accuracy is 93.1−99.7% |
Accuracy of estimation of age better in lower age groups than in higher groups. |
8. | Santini et al (1990)11 | n = 60 | Chinese (caries-free skulls) | Miles and Brothwell |
r= 0.46 SEE 9.2–9.7 years |
Dental wear does not proceed at the same rate in all the three molars. Does not give a precise estimate of age at death. |
9. | Dreier FG (1994)21 | n=143 | Arikara remains (USA) |
Dreier and Scott (New method) | r=0.945−0.946 | Suitable for age 35–40 years Sex differences exist. Females show more variability. |
10 | Li and Ji (1995)1 | n= 633 Age: 15–71 years |
Chinese (skulls) | ASA method | r = 0.94–0.97 | One molar is sufficient to estimate age at death. |
11 | Constandse-Westermann (1997)22 | n=109 | Zwolle, Netherlands | Pot method |
r not applicable SEE: 3.8 males and 6.3 females |
Based on the average rate of attrition of the total sample/population high percentage of correct classification into four age classes can be obtained. |
12 | Kim et al (2000)3 | n=383 Age: 13–79 years |
Korean population (casts of living individuals of known age) | Kim’s scoring criteria |
r= 0.6645 −0.757 in males 0.639 −0.8193 in females SEE: 1.52 yrs |
Simple reliable method. Accuracy of ± 2–3 years in individuals <25 years. |
13 | Ajmal et al (2001)2 | n=100 Age: 21-60 years |
Mangalore, India | Li and Ji method |
r not reported SEE: 2.76–3.94 |
Shown ASA method is suitable for the Indian population. |
14 | Oliveira et al (2006)23 | n= 298 | Prehistoric Brazilian population | Brothwell chart |
r not applicable SEE: 8.22 |
Satisfactory results. |
15 | Yun et al (2007)24 (Modified Kim’s scoring system) | n=1092 (pairs of maxillary and mandibular casts) | Korean population (casts) | Modified Kim’s scoring system (changed the selection of teeth and degree of classification) |
r = 0.903 in males 0.917 in females SEE: 7.28 and 7.16, respectively |
Reliable and accurate method. Estimation of any age above 20 years. |
16 | Gilmore et al (2012)9 (Modification of Miles method) | n = 311 | Hunter-gatherers and pastoralist populations with diverse population histories and diets | Modified Miles method | SEE: 5.4 years | A viable option for age estimation in skeletal samples. Better than cranial suture closure method. |
17 | Telang et al (2014)25 | n=120 Casts Age: 13–70 years |
Mysore, India | Kim’s scoring criteria |
r =0.898−0.959 SEE: 73.3%–76.6% estimated with an error of ±5 years |
Indian population high level of accuracy. |
18 | Vieira et al (2015)14 | n= 223 | Indigenous Amazon population | Modified tooth wear index from Mockers O et al 2004 |
r =0.316 for Urban population SEE: 6.9 years |
Poor correlation with age in urban populations. A strong relationship with age in indigenous amazon populations. |
19 | Lu et al (2017)26 | n=190 Age: 16–62 years |
Chinese Malaysian adults | Modified Kim’s index |
r = 0.906 and 0.86 for males and females SEE: 7.37 and 7.26, respectively |
Fairly accurate in individuals <40 years of age. Accuracy decreases with age. |
20 | Faillace et al (2017)7 | n=620 Age: >15 years |
New Mexico (Individuals from different background) | Yun et al (Modified Kim’s scoring) Prince et al |
r = 0.512 SEE: 7.5 years |
Age estimation from dental wear possible for modern industrialized populations. Better correlation in individuals <45 years of age. Increasingly unreliable in older individuals. |
21 | Santini et al (2017)27 | n= 50 Age: 16–62 years |
Chinese | Miles method | 86% Estimated within 5 years | Fairly accurate in individuals less than 40 years but accuracy decreases with increase in age. |
22 | Alayan et al (2018)28 | n=50 | Chinese skulls | Brothwell chart |
r not applicable Accuracy of 88% |
Can be used as a reasonable method of age estimation. Tooth wear assessment between various assessors was precise. |
23 | Bartholdy et al (2019)29 | n= 951 Age: 1–19 years |
The Netherlands (post-medieval cemetery) | Smith’s scoring |
r=0.964 SEE: 1.4 years |
Recording of non-adult dental wear. |
24 | The present study (2020) | n = 136 Age: 20–70 years |
Dakshina Kannada population | Li and Ji method |
r = 0.631 SEE: 9.231 years |
In younger age group <30 years more accurate. Can categorize fairly into age groups. |