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May 2001
Volume 42, Issue 6
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Clinical and Epidemiologic Research  |   May 2001
The Relationship between Ocular Dimensions and Refraction with Adult Stature: The Tanjong Pagar Survey
Author Affiliations
  • Tien Yin Wong
    From the Singapore National Eye Centre and the Singapore Eye Research Institute; the
    Department of Ophthalmology, National University of Singapore; the
    Department of Ophthalmology and Visual Sciences, University of Wisconsin, Madison; and the
  • Paul J. Foster
    Department of Epidemiology and International Eye Health, Institute of Ophthalmology, University College London, United Kingdom.
  • Gordon J. Johnson
    Department of Epidemiology and International Eye Health, Institute of Ophthalmology, University College London, United Kingdom.
  • Barbara E. K. Klein
    Department of Ophthalmology and Visual Sciences, University of Wisconsin, Madison; and the
  • Steve K. L. Seah
    From the Singapore National Eye Centre and the Singapore Eye Research Institute; the
Investigative Ophthalmology & Visual Science May 2001, Vol.42, 1237-1242. doi:
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      Tien Yin Wong, Paul J. Foster, Gordon J. Johnson, Barbara E. K. Klein, Steve K. L. Seah; The Relationship between Ocular Dimensions and Refraction with Adult Stature: The Tanjong Pagar Survey. Invest. Ophthalmol. Vis. Sci. 2001;42(6):1237-1242.

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Abstract

purpose. To describe the association of ocular dimensions and refraction with adult stature.

methods. This was a population-based cross-sectional survey of adult Chinese aged 40 to 81 years residing in the Tanjong Pagar district in Singapore. As part of the examination, ocular dimensions, including axial length, anterior chamber depth, lens thickness, and vitreous chamber depth, were measured using an A-mode ultrasound device. Corneal radius and refraction were determined with an autorefractor, with refraction further refined subjectively. Height (in meters) and weight (in kilograms) were measured using a standardized protocol, and body mass index (BMI) was calculated as weight divided by the square of the height (kilograms per square meter).

results. Data on ocular biometry, refraction, height, and weight were available on 951 (55.4%) participants with phakic eyes. After controlling for age, sex, education, occupation, housing type, income, and weight, it was found that taller persons were more likely to have longer axial lengths (+0.23 mm longer axial length, for every 0.10 m difference in height), deeper anterior chambers (+0.07 mm), thinner lenses (−0.09 mm), longer vitreous chambers (+0.26 mm), and flatter corneas (+0.09 mm longer corneal radius), although refractions were similar. In contrast, heavier persons tended to have more hyperopic refractions (+0.22 D for every 10 kg difference in weight, +0.56 D for every 10 kg/m2 difference in BMI) but similar ocular dimensions.

conclusions. Adult height is independently related to ocular dimensions, but does not appear to influence refraction. Thus, although taller persons are more likely to have longer globes, they also tend to have deeper anterior chambers, thinner lenses, and flatter corneas. Conversely, weight is independently related to refraction, although the exact biometric component responsible for this association is not apparent.

Axial length of the globe has been shown to increase early in life, concomitant with overall growth and development of the child. 1 2 3 However, the relationship between ocular dimensions and adult stature is not clear. Data on the association between refraction and stature are inconsistent. Whereas some studies have indicated that myopia appears to be more common in taller 4 5 6 7 8 9 10 and heavier 5 6 7 8 persons, suggesting that axial lengths are longer among these people, other studies have found no association. 11 12 13 14 15 The discrepancy among these studies may be due to a combination of small sample sizes, selection bias in clinic-based studies, differing myopia definitions, and other methodologic variations (e.g., refraction and stature based on interview data). 
Regardless, any association between refraction and stature is likely to be complex, because the final refractive state of an eye is dependent on an intricate emmetropization process, involving the interaction between individual ocular biometric components (i.e., axial ocular dimensions, corneal curvature, and lenticular power). 16 Thus, even if stature is associated with an individual biometric component (for example, axial length), the effects of other components (for example, corneal curvature) may compensate and even attenuate the overall association between stature and refraction. 
Few studies have evaluated directly the relationship between ocular dimensions and adult stature. In Labrador, Johnson et al. 17 observed a positive correlation between axial length and height. However, the association with other ocular components was not reported in that study and is largely unknown. 
Recently, we conducted a population-based survey of ocular disorders in adult Chinese residents in Singapore. 18 19 The variation in ocular biometry with age and sex and its effect on refraction in this population have been reported. 20 In the present analysis, we describe the relation of ocular dimensions and refraction with stature in adults. 
Methods
Study Population
The Tanjong Pagar Survey is a population-based cross-sectional survey of ocular disorders among adult Chinese living in Singapore between October 1997 and August 1998. Detailed population selection and methodology have been reported. 18 19 20 In brief, the 1996 Singapore electoral register in the district of Tanjong Pagar was used as the sampling frame in this study. Because Tanjong Pagar cuts across a large cross-section of smaller local areas with diverse social and economic backgrounds, it is not unreasonable to regard the sample as fairly representative of other regions in Singapore. The electoral register listed 15,082 Chinese persons aged between 40 and 79 years residing in the district. Two thousand (13.3%) persons were initially selected by using a stratified, clustered, random sampling method (with more weight given to the older age groups). This involved selecting residents randomly, 500 from each of four age strata—40 to 49, 50 to 59, 60 to 69, and 70 to 79 years—residing in 50 area clusters (of a total of 84) defined by street name and located within specified boundaries of the predesignated study clinic. The area clusters selected were those with the largest concentration of persons in the district (82% of the population). 
Among the 2000 persons selected, 46 had died, 235 had moved to addresses outside the district before the study period, and 2 were excluded on grounds of ill health, leaving 1717 subjects considered eligible to participate in this study. These persons were invited to undergo a comprehensive eye examination at the study clinic, after which an abbreviated home examination on nonrespondents was conducted. The total number of subjects examined in either setting was 1232 (71.8%), but only subjects examined in the study clinic (n= 1090, 63.5%) had a biometric examination. Of these, 80 had had cataract extraction in the right eye, and a further 59 had incomplete data on biometry, refraction, height, or weight, leaving 951 (55.4%) subjects to be included in this analysis. Table 1 shows the characteristics of these participants and those excluded. In general, subjects included in our analysis were younger, taller, and heavier; had higher education levels; were more likely to be professionals and office workers, production operators, or salespeople; lived in better housing; and had higher individual income. 
Procedures
The examination procedures followed a standardized protocol described elsewhere. 18 20 During the examination, height was measured with the person standing up without shoes and recorded in meters. Weight without shoes was measured on a single automatic weighing scale and recorded in kilograms. Body mass index (BMI) was derived from the ratio of the person’s weight divided by the square of the person’s height and recorded in kilograms per square meter. Sociodemographic information, including education, occupation, housing type, and income, were ascertained from a standardized interview. 
Ocular biometry and refraction were performed as follows. Measurements of axial length (AL), anterior chamber depth (ACD), lens thickness (LT), and vitreous chamber depth (VCD) were obtained using a 10-MHz A-mode ultrasound device (Compuscan; Storz, St. Louis, MO). The hard-tipped, corneal contact ultrasound probe was mounted on a tonometer (Haag–Streit, Bern, Switzerland) set to the person’s intraocular pressure. The mean of 16 separate readings was recorded, together with the SD of each parameter. Corneal curvature radius (CR) was assessed using a hand-held autorefractor-keratometer (Retinomax K-plus; Nikon, Tokyo, Japan). The device recorded eight separate estimates of corneal curvature along two meridians, each 90° apart. A mean value along each meridian was recorded, and the mean CR was calculated as the average of the greater and lesser radius of the curvature. Noncycloplegic objective refraction was assessed with the same handheld autorefractor used to measure CR, after which a single optometrist performed a subjective refinement of the refraction with a phoropter, using the results of the objective refraction. Lens nuclear opacity (NO) was graded at a slit lamp biomicroscope (Model BQ 900; Haag–Streit), using the modified Lens Opacity Classification System III (LOCS III) score. 21  
Definitions
Age was defined as the age at the time of examination. Education was ascertained by the question, “What was your highest education level?” and categorized as follows: no formal education, primary (6 years or less), secondary (7–10 years), and tertiary (11 years or more, including university education). Occupation was ascertained with the question, “What group of occupations do you feel best categorizes your job?” with the response allocated to one of 12 groups, and recategorized into 6 groups as follows: (1) managers, professionals, and officer workers; (2) salespersons; (3) machine operators and production workers; (4) laborers, cleaners, and agricultural workers; (5) homemakers; and (6) none of the above. Housing type was classified as follows: one- or two-room government flats, three-room government flats, four- to five-room government flats, executive government flats, and private housing. Individual monthly income was based on Singapore dollars (approximate exchange rate, Sing$1.7 = US$1). 
Statistical Analysis
Because the correlations between the two eyes for the refractive and biometric variables were high (e.g., correlation coefficients between right and left eyes for spherical equivalents = 0.85, AL = 0.85, and VCD = 0.86) and the results were similar between the two eyes, only the data from analyses of the right eye are presented. Data on noncycloplegic refraction were converted to spherical equivalent diopters and were based on subjective refraction, when participants had both subjective and objective refraction, and on objective refraction, when only that information was available. Overall agreement between both types of refraction was high. 19  
The analysis was conducted as follows. First, univariate associations between height, weight, and BMI with different ocular biometric components, refraction, and sociodemographic factors were determined. Next, simple linear regressions were performed to assess the effect of height, weight, and BMI (independent variables) on the individual biometric components and refraction (dependent variables). Multiple linear regression models were then constructed to evaluate the effects of height, weight, and BMI on individual biometric components and refraction, controlling in turn for age and sex; age, sex, and education; and age, sex, education, and socioeconomic indicators (occupation, housing, and income). The adequacy of all linear regression models was assessed by plotting the residuals of the regression model against the independent variables and also against the predicted values of the dependent variable (predicted fit). Because height correlated strongly with weight, they were both entered simultaneously in regression models to determine whether their effects were independent of each other. Statistical analyses of the data were performed on computer with statistical analysis software (SPSS, Chicago, IL). Results are expressed as means ± SD. 
This study was approved by the ethics committee of Singapore National Eye Center and performed in accordance with the tenets of the World Medical Association’s Declaration of Helsinki. 
Results
Among the 951 participants, the mean height, weight, and BMI were 1.59 ± 0.08 m, 59.9 ± 11.1 kg, and 23.8 ± 3.7 kg/m2, respectively. The correlations of height, weight, and BMI with sociodemographic and ocular biometric variables in the study population are shown in Table 2 . Height correlated positively with education, income, AL, ACD, VCD, and CR and negatively with age, female sex, LT, and NO; it did not correlate with either housing type or refraction. Weight correlated with similar variables as height, with the exception of housing or refraction. BMI correlated negatively with education and positively with refraction, but did not correlate with other variables. 
Table 3 shows the mean values of ocular biometric components among persons categorized by quintiles of height, weight, and BMI. In general, taller and heavier persons had longer ALs, deeper ACDs, longer VCDs, flatter corneas, thinner lenses, and less severe NO than did shorter persons. Height and weight were not associated with refraction. In contrast, a higher BMI was associated with less “minus” refraction, but not with ocular biometric components. 
Regression models as described in the Methods section are presented in Table 4 . Each value in the table represents the results of a separate regression model, with individual ocular biometric components or refraction as the dependent variable, and height, weight, or BMI as the independent variable in the model, either alone or with other covariates. For example, the relation between height and AL is presented in the first line of the table as four separate regression models. In the first model, a person 0.10 m taller could be expected to have a 0.42-mm longer AL than a shorter person. In the next two models, after controlling first for age and sex and then further for education, the difference in AL declined to 0.28 mm and 0.24 mm, respectively. In the final model, after age, sex, education, socioeconomic indicators, and weight are controlled for, a taller person was still more likely to have a 0.23-mm longer AL than someone 0.10 m shorter. In general, taller persons were more likely to have longer ALs, deeper ACDs, longer VCDs, flatter corneas, and thinner lenses than shorter persons of similar age, sex, education level, socioeconomic status, and weight. However, height was not independently associated with NO or final refraction. 
With regard to weight, a person 10 kg heavier was more likely to have a longer AL, deeper ACD, longer VCD, flatter cornea, thinner lens, more severe NO, and more “plus” refraction than a lighter person. However, after age and sex were controlled for, only associations with ACD, CR, and refraction persisted. After education, socioeconomic indicators and height were further controlled for, weight was associated only with refraction, but not with other variables. A person 10 kg heavier than another was more likely to have a hyperopic refraction (0.22 D). The pattern of association for BMI was similar to that for weight, with refraction as the only independent variable associated with BMI. 
Adequacy of all regression models were checked by plotting the residuals of the models against independent variables and the predicted fit (as described in the Methods section). These residuals were randomly and homogenously distributed in these plots, suggesting that the models were appropriate (plots not shown). 
Additional analyses using the average of ocular measures of right and left eyes were conducted but did not substantially alter the result of our analysis using right eyes only (data not shown). We also tested age (40–59 versus 60–81 years) and gender interaction, first by stratification and then by adding an interaction term in the regression models. Interaction was neither substantial nor statistically significant (P > 0.10). 
Discussion
The relationship of adult stature with ocular dimensions and refraction is not clear but may be useful in understanding the intricate development and maintenance of emmetropia throughout life. Earlier studies have suggested a possible relation between adult stature and refraction, because taller and heavier persons were observed to be more myopic than shorter and lighter persons. 4 5 6 7 8 9 10 One common hypothesis is that taller persons have larger globes and longer ALs and therefore higher rates of myopia than shorter persons. This was partly based on the premise that the eye changes in size early in life and during childhood, concomitant with overall growth and development, 1 2 3 and the age of cessation of axial elongation was similar to the age of cessation of increase in height (both ∼13 years). 22 However, actual data documenting a positive relationship between adult height and AL are limited. 17  
A separate but related hypothesis to explain a possible relation between stature and myopia avoids any assumptions about globe size. The hypothesis is that, because taller (and heavier) persons are more likely to come from higher socioeconomic backgrounds and have better nutrition, higher education levels, and occupations associated with a greater amount of near work activities (e.g., professionals), these persons have a higher risk of myopia, irrespective of the anatomic mechanisms of myopia. Height and weight are thus considered surrogate markers for other risk factors of myopia. This hypothesis is supported by studies that show an attenuation of the association between stature and myopia, after controlling for education and intelligence 11 or occupation. 7  
However, other studies, including a large population-based survey, have not found any relationship between adult stature and refraction. 11 12 13 14 15 Although the inconsistency among results of these studies may be due to methodological variations, 4 5 6 7 8 9 10 11 12 13 14 15 it is conceivable that a person’s height, in fact, has no bearing on refractive status. Consistent with this are observations that the distribution of height in a given population is gaussian, but the distribution of refraction is usually leptokurtic (with an excess near emmetropia). 23  
Our study provides population-based data that may help explain some of these observations. First, we found that height in Chinese was independently related to all ocular biometric components, even after controlling for age, sex, education, occupation, income, housing type, and weight. On average, taller persons tended to have longer ALs, deeper ACDs, and longer VCDs, but thinner lenses and flatter corneas than did shorter people. Between two persons with a 0.10-m difference in height, the taller person could be expected to have nearly a 0.25-mm longer AL and VCD. As a result, longer ALs and VCDs among taller persons may explain some of the previous associations between height and myopia. Moreover, because the association between height and AL or VCD remained even after controlling for education and socioeconomic indicators, height does not appear to be solely a marker for risk of myopia, as some have hypothesized. 
More important, we found that height did not appear to influence refraction, although it was strongly related to axial dimensions (i.e., although taller persons tended to have longer globes, they were not necessarily more myopic). A detailed examination of the data suggests that this may be related to the compensatory hyperopic effects of a deeper ACD, thinner lenses, and flatter corneas in taller people. This observation supports the concept that the eye’s refractive state is determined by a delicate balance between ocular dimensions and the refracting power of different components, controlled by both passive and active (visual feedback) mechanisms. 16 24 25 26 Similar compensatory changes (i.e., flatter corneas, deeper anterior chamber depths, and thinner lens) in emmetropic eyes with longer ALs have been noted in non–population-based studies. 27 28 29 30 Data in infants and children have shown that the eye is capable of achieving emmetropia despite dramatic changes in eyeball size during growth and development. 31 It is therefore possible that the eye maintains an emmetropic refraction, even when subjected to variation in eyeball size related to variation in a person’s height. 
The relation between weight and BMI with refraction, but not with any obvious ocular biometric variable, is more difficult to explain. BMI is an anthropometric measure that de-emphasizes the effect of height on body weight and correlates closely with the degree of obesity. In our study, weight and BMI behaved similarly. Heavier and more obese (higher BMI) persons were more likely to be hyperopic than were lighter, leaner persons, although the magnitude of hyperopia was small (between 0.25 and 0.50 D for every 10 kg and 10 kg/m2 difference in weight and BMI, respectively). Previous studies have not shown a consistent relationship between weight and refraction. Whereas some have documented an association with myopia, 5 6 7 8 others have found an association with hyperopia instead. 12 Because weight correlates highly with age, sex, and height, the apparent relationship between weight and refractive errors in these studies may also be due to the confounding effects of these factors. 
However, the association in our study was independent of these factors. Our data did not reveal the exact ocular component responsible for the observed relation of weight and BMI to refraction. One possible explanation is that the combined effects of minor unobservable variations in individual components produced an overall observable difference in final refraction between persons of different weights and BMIs. Of the major individual determinants of refraction (AL or VCD, corneal curvature, and lenticular power), lenticular power is perhaps inadequately represented in our study by LT and lens NO. It is possible that heavier and more obese persons have lenticular changes that affect final refraction. 32 33 34  
We are also unable to provide an adequate explanation for the apparent discrepancy between the patterns of association of height (associated with biometric components, but not refraction) versus weight and BMI (associated only with refraction) in our study. However, similar discrepancies in the association with refractive status have been noted previously. 9 12 Both height and weight are dependent on complex genetic and environmental influences (e.g., nutritional, metabolic) throughout infancy, childhood and adult life. Thus, the discrepancy between height and weight in our study was not totally unexpected. 
The principal strength of this study was the population-based random sampling strategy, which avoided potential biases seen in the previous studies in specific, highly selected population groups, such as military personnel. 10 11 12 Some important limitations warrant consideration. First, we were unable to control for unmeasured potential confounders of the associations of stature with ocular dimension and refraction. For example, we did not have data on socioeconomic factors during childhood, family histories of height and refractive status, or documentation of near work activities, all of which may be important. Second, selection bias may have accentuated some findings and masked others. Although the overall participation rate in our survey was 71.8%, full data were available for only 55%, and our observations could be explained if taller and more hyperopic persons were selectively excluded from our study population, perhaps because of higher cataract extraction rates (biometric data on participants with pseudophakic and aphakic eyes were not analyzed), higher mortality, or other unknown reasons for nonparticipation. Third, these data were cross-sectional, with all parameters measured at one time point. Many of these (e.g., height, weight, and refraction) change over time, and it is uncertain whether the longitudinal relationships are similar. Finally, it is uncertain how these data apply to white and black populations elsewhere. 15 32 33 34 It is possible that the associations seen in our Chinese population in Singapore differ from other ethnic groups with dissimilar genetic and environmental exposures, different distributions of height and weight, and lower rates of myopia. 
In conclusion, we found that taller persons tended to have longer ALs and vitreous chamber depths than shorter persons. However, refraction between tall and short people appeared to be similar, perhaps because of compensating effects of deeper anterior chambers, thinner lenses, and flatter corneas among taller persons. On the other hand, heavier persons were mildly more hyperopic, although the exact ocular component that is responsible for this association is not apparent. 
Table 1.
 
Comparison of Subjects Included and Excluded from Analyses
Table 1.
 
Comparison of Subjects Included and Excluded from Analyses
Included (n = 951) Excluded (n = 281) P
n Mean n Mean
Age (y) 951 58.1 281 66.5 <0.001
Refraction right eye (D)* 951 −0.49 262 −0.36 0.52
Height (m)* 951 1.59 131 1.56 0.02
Weight (kg)* 950 59.9 131 54.5 <0.001
n % n % P
Women 519 54.5 156 55.7 0.72
Education*
No education 227 24.1 97 36.6 <0.001
Primary 381 40.1 116 43.8
Secondary 267 28.1 43 16.2
Tertiary 74 7.8 9 3.4
Housing*
1–2 room flats 163 17.2 72 26.8 <0.001
3 room flats 515 54.4 143 53.2
4–5 room flats 248 26.2 51 18.0
Executive flats 17 1.8 2 0.7
Private housing 4 0.4 1 0.3
Individual monthly income*
Less than $1000 562 59.9 214 80.1 <0.001
$1000–2000 173 18.4 21 7.9
$2000–3000 62 6.6 3 1.2
More than $3000 47 5.0 4 1.5
Retired 95 10.1 25 9.4
Occupation*
Professionals and managers 127 13.4 20 7.4 <0.001
Office workers 65 6.8 12 4.4
Machine operators 103 10.9 31 11.4
Sales persons 162 17.1 32 11.8
Production workers 90 9.5 33 12.2
Laborers and cleaners 129 13.6 48 17.7
Homemakers 214 22.6 78 28.8
Unemployed 30 3.2 12 4.4
Not classifiable 29 3.1 5 1.8
Table 2.
 
Correlation between Stature (Height, Weight, and BMI) and Sociodemographic Variables, Ocular Biometry and Refraction
Table 2.
 
Correlation between Stature (Height, Weight, and BMI) and Sociodemographic Variables, Ocular Biometry and Refraction
Spearman Rank Correlation Coefficient
Height (m) Weight (kg) BMI (kg/m2)
Sociodemographic variables
Age (y) −0.178, † −0.095, ‡ 0.015
Sex (women) −0.711, † −0.367, † 0.033
Education 0.322, † 0.080, § −0.122, †
Housing 0.038 0.039 0.008
Individual monthly income 0.337, † 0.185, † 0.005
Ocular biometry and refraction
SE (D) −0.040 0.058 0.100, ‡
AL (mm) 0.333, † 0.157, † −0.035
ACD (mm) 0.311, † 0.183, † −0.005
LT (mm) −0.242, † −0.139, † 0.004
VCD (mm) 0.320, † 0.135, † −0.050
CR (mm) 0.301, † 0.201, † 0.049
NO (LOCS III score* ) −0.187, † −0.116, † −0.009
Table 3.
 
Ocular Biometry and Refraction by Stature
Table 3.
 
Ocular Biometry and Refraction by Stature
Stature Range n AL (mm) ACD (mm) LT (mm) VCD (mm) CR (mm) NO (LOCS III* ) SE (D)
Height (m)
1st Quintile 1.37–1.50 190 22.74 ± 0.9 2.70 ± 0.4 4.92 ± 0.5 15.13 ± 0.9 7.55 ± 0.3 3.5 ± 0.9 −0.24 ± 2.3
2nd Quintile 1.51–1.55 194 23.05 ± 1.2 2.86 ± 0.4 4.78 ± 0.5 15.40 ± 1.1 7.57 ± 0.2 3.2 ± 0.8 −0.60 ± 2.8
3rd Quintile 1.56–1.59 186 23.19 ± 1.2 2.83 ± 0.4 4.78 ± 0.5 15.59 ± 1.2 7.66 ± 0.3 3.1 ± 0.9 −0.49 ± 2.7
4th Quintile 1.60–1.65 196 23.44 ± 1.1 2.99 ± 0.4 4.68 ± 0.5 15.77 ± 1.1 7.68 ± 0.3 3.2 ± 0.9 −0.60 ± 2.7
5th Quintile 1.66–1.83 185 23.78 ± 1.1 3.10 ± 0.4 4.63 ± 0.5 16.06 ± 1.1 7.79 ± 0.3 2.9 ± 0.8 −0.52 ± 2.4
P < 0.001 P < 0.001 P < 0.001 P < 0.001 P < 0.001 P < 0.001 P = 0.44
Weight (kg)
1st Quintile 29.6–50.4 190 22.99 ± 1.2 2.79 ± 0.4 4.83 ± 0.4 15.38 ± 1.1 7.57 ± 0.3 3.3 ± 1.0 −0.90 ± 3.0
2nd Quintile 50.6–56.0 185 23.13 ± 1.2 2.82 ± 0.4 4.82 ± 0.5 15.50 ± 1.1 7.61 ± 0.2 3.2 ± 0.8 −0.51 ± 2.7
3rd Quintile 56.2–61.8 198 23.33 ± 1.1 2.90 ± 0.4 4.73 ± 0.5 15.70 ± 1.1 7.67 ± 0.2 3.2 ± 0.9 −0.55 ± 2.6
4th Quintile 62.0–68.6 185 23.28 ± 1.2 2.94 ± 0.4 4.74 ± 0.5 15.60 ± 1.2 7.68 ± 0.3 3.1 ± 0.8 −0.15 ± 2.4
5th Quintile 68.8–113.0 192 23.44 ± 1.1 3.02 ± 0.4 4.67 ± 0.5 16.74 ± 1.0 7.71 ± 0.3 3.0 ± 0.8 −0.33 ± 2.2
P < 0.001 P < 0.001 P < 0.001 P = 0.001 P < 0.001 P = 0.001 P = 0.16
BMI (kg/m2)
1st Quintile 14.0–20.5 190 23.29 ± 1.2 2.89 ± 0.4 4.73 ± 0.5 15.67 ± 1.2 7.63 ± 0.3 3.1 ± 0.9 −1.08 ± 2.9
2nd Quintile 20.6–22.7 190 23.34 ± 1.2 2.94 ± 0.4 4.72 ± 0.4 15.68 ± 1.1 7.65 ± 0.2 3.1 ± 0.8 −0.54 ± 2.8
3rd Quintile 22.8–24.5 190 23.26 ± 1.3 2.86 ± 0.5 4.80 ± 0.5 15.59 ± 1.2 7.66 ± 0.3 3.4 ± 0.9 −0.56 ± 2.6
4th Quintile 24.6–26.7 190 23.10 ± 1.0 2.91 ± 0.5 4.76 ± 0.5 15.45 ± 1.0 7.67 ± 0.2 3.0 ± 0.8 −0.07 ± 2.2
5th Quintile 26.8–41.5 190 23.18 ± 1.1 2.88 ± 0.4 4.77 ± 0.4 15.53 ± 1.0 7.65 ± 0.3 3.2 ± 0.8 −0.19 ± 2.4
P = 0.10 P = 0.55 P = 0.26 P = 0.048 P = 0.34 P = 0.84 P < 0.001
Table 4.
 
Linear Regression Models of Ocular Biometry and Refraction by Height, Weight, and BMI
Table 4.
 
Linear Regression Models of Ocular Biometry and Refraction by Height, Weight, and BMI
Crude Data P Adjusted for Age and Sex P Adjusted for Age, Sex, and Education P Adjusted for Age, Sex, Education, SES and Weight or Height, † P R2 Final Models, ‡
Height (0.10-m difference)
AL (mm) 0.42 (0.33, 0.51)* <0.001 0.28 (0.15, 0.40) <0.001 0.24 (0.12, 0.36) <0.001 0.23 (0.10, 0.37) 0.001 0.167
ACD (mm) 0.16 (0.13, 0.20) <0.001 0.09 (0.04, 0.13) <0.001 0.08 (0.04, 0.12) <0.001 0.07 (0.02, 0.12) 0.004 0.239
LT (mm) −0.13 (−0.16, −0.09) <0.001 −0.09 (−0.12, −0.04) <0.001 −0.08 (−0.12, −0.04) <0.001 −0.09 (−0.14, −0.04) <0.001 0.298
VCD (mm) 0.39 (0.30, 0.47) <0.001 0.28 (0.16, 0.40) <0.001 0.24 (0.13, 0.36) <0.001 0.26 (0.13, 0.38) <0.001 0.173
CR (mm) 0.10 (0.08, 0.12) <0.001 0.10 (0.07, 0.12) <0.001 0.10 (0.07, 0.12) <0.001 0.09 (0.05, 0.12) <0.001 0.103
NO (LOCS III) −0.20 (−0.27, −0.13) <0.001 −0.09 (−0.16, −0.02) 0.014 −0.08 (−0.15, −0.01) 0.021 −0.07 (−0.14, 0.01) 0.09 0.514
SE (D) −0.09 (−0.30, 0.11) 0.36 0.12 (−0.16, 0.41) 0.39 0.21 (−0.06, 0.49) 0.13 0.08 (−0.23, 0.38) 0.63 0.130
Weight (10-kg difference)
AL (mm) 0.14 (0.07, 0.21) <0.001 0.03 (−0.04, 0.10) 0.39 0.05 (−0.01, 0.12) 0.12 −0.002 (−0.08, 0.007) 0.95 0.167
ACD (mm) 0.07 (0.05, 0.10) <0.001 0.03 (0.01, 0.05) 0.04 0.03 (0.01, 0.05) 0.02 0.01 (−0.01, 0.04) 0.34 0.239
LT (mm) −0.05 (−0.07, −0.02) 0.001 −0.01 (−0.04, 0.01) 0.39 −0.01 (−0.04, 0.01) 0.34 0.008 (−0.02, 0.04) 0.54 0.298
VCD (mm) 0.11 (0.05, 0.18) <0.001 0.02 (−0.05, 0.08) 0.63 0.04 (−0.03, 0.10) 0.25 −0.02 (−0.09, 0.05) 0.52 0.173
CR (mm) 0.05 (0.03, 0.06) <0.001 0.03 (0.01, 0.05) <0.001 0.03 (0.01, 0.05) <0.001 0.01 (−0.01, 0.03) 0.21 0.103
NO (LOCS III) −0.10 (−0.15, −0.05) <0.001 −0.03 (−0.07, 0.01) 0.095 −0.04 (−0.07, 0.01) 0.066 −0.02 (−0.06, 0.02) 0.32 0.514
SE (D) 0.18 (0.03, 0.32) 0.021 0.28 (0.13, 0.44) <0.001 0.24 (0.08, 0.39) 0.002 0.22 (0.05, 0.39) 0.01 0.130
BMI (10-kg/m2 difference)
AL (mm) −0.11 (−0.31, 0.09) 0.27 −0.09 (−0.28, 0.11) 0.38 −0.01 (−0.18, 0.20) 0.91 0.01 (−0.18, 0.20) 0.91 0.153
ACD (mm) 0.01 (−0.07, 0.08) 0.83 0.02 (−0.05, 0.08) 0.61 0.03 (−0.03, 0.10) 0.32 0.03 (−0.03, 0.10) 0.35 0.230
LT (mm) 0.03 (−0.05, 0.11) 0.46 0.03 (−0.04, 0.10) 0.39 0.03 (−0.04, 0.09) 0.48 0.02 (−0.04, 0.09) 0.49 0.289
VCD (mm) −0.16 (−0.35, 0.03) 0.11 −0.13 (−0.31, 0.05) 0.15 −0.05 (−0.22, 0.13) 0.61 −0.04 (−0.22, 0.13) 0.64 0.156
CR (mm) 0.02 (−0.02, 0.04) 0.38 0.03 (−0.02, 0.07) 0.22 0.03 (−0.02, 0.07) 0.20 0.03 (−0.01, 0.08) 0.18 0.062
NO (LOCS III) −0.06 (−0.21, 0.09) 0.47 −0.04 (−0.15, 0.06) 0.41 −0.06 (−0.17, 0.05) 0.27 −0.06 (−0.17, 0.04) 0.25 0.511
SE (D) 0.76 (0.31, 1.21) 0.001 0.78 (0.35, 1.21) <0.001 0.58 (0.15, 1.00) 0.008 0.56 (0.14, 0.98) 0.01 0.128
 
The authors thank David Machin and Tze-Pin Ng for statistical help and advice; Judy Hall for training technical staff and providing quality assurance services; and Rachel Ng, Bernie Poh, and the Clinical Audit department, Singapore National Eye Center, for data collection and analysis. 
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