December 2005
Volume 46, Issue 12
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Clinical and Epidemiologic Research  |   December 2005
Risk Factors for Age-Related Macular Degeneration: Findings from the Andhra Pradesh Eye Disease Study in South India
Author Affiliations
  • Sannapaneni Krishnaiah
    From the L. V. Prasad Eye Institute, Banjara Hills, Hyderabad, India.
  • Taraprasad Das
    From the L. V. Prasad Eye Institute, Banjara Hills, Hyderabad, India.
  • Praveen K. Nirmalan
    From the L. V. Prasad Eye Institute, Banjara Hills, Hyderabad, India.
  • Rishita Nutheti
    From the L. V. Prasad Eye Institute, Banjara Hills, Hyderabad, India.
  • Bindiganavale R. Shamanna
    From the L. V. Prasad Eye Institute, Banjara Hills, Hyderabad, India.
  • Gullapalli N. Rao
    From the L. V. Prasad Eye Institute, Banjara Hills, Hyderabad, India.
  • Ravi Thomas
    From the L. V. Prasad Eye Institute, Banjara Hills, Hyderabad, India.
Investigative Ophthalmology & Visual Science December 2005, Vol.46, 4442-4449. doi:10.1167/iovs.05-0853
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      Sannapaneni Krishnaiah, Taraprasad Das, Praveen K. Nirmalan, Rishita Nutheti, Bindiganavale R. Shamanna, Gullapalli N. Rao, Ravi Thomas; Risk Factors for Age-Related Macular Degeneration: Findings from the Andhra Pradesh Eye Disease Study in South India. Invest. Ophthalmol. Vis. Sci. 2005;46(12):4442-4449. doi: 10.1167/iovs.05-0853.

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Abstract

purpose. To assess prevalence, potential risk factors, and population attributable risk percentage (PAR%) for age-related macular degeneration (AMD) in the Indian state of Andhra Pradesh.

methods. A population-based study, using a stratified, random, cluster, systematic sampling strategy, was conducted in the state of Andhra Pradesh in India from 1996 to 2000. Participants from 94 clusters in one urban and three rural areas representative of the population of Andhra Pradesh underwent a detailed interview and a detailed dilated ocular evaluation by trained professionals. In this report, the authors present the prevalence estimates of AMD and examine the association of AMD with potential risk factors in persons aged 40 to 102 years (n = 3723). AMD was defined according to the international classification and grading system. Standard bivariate and multivariate analyses were performed to identify the potential risk factors for AMD. PAR% was calculated by Levin’s formula.

results. AMD was present in 71 subjects—an age-gender-area–adjusted prevalence of 1.82% (95% confidence interval [CI], 1.39%–2.25%). Risk factors that were significant in bivariate analyses were considered for multivariate logistic regression analysis. Multivariate analysis showed that the adjusted prevalence of AMD was significantly higher in those 60 years of age or older (odds ratio [OR], 3.55; 95% CI, 1.61–7.82) and history of prior cigar smoking (OR, 3.29; 95%CI, 1.42–7.57). Presence of cortical cataract and prior cataract surgery were significantly associated with increased prevalence of AMD (adjusted OR, 2.87; 95% CI, 1.57–5.26 and 3.79; 95% CI, 2.1–6.78), respectively. The prevalence of AMD was significantly lower in light alcohol drinkers (adjusted OR, 0.38; 95% CI, 0.19–0.76) compared with nondrinkers. The PAR% for hypertension and heavy cigar smoking was 10% and 14%, respectively, in this population.

conclusions. The prevalence of AMD in this south Indian population is similar to those reported in other developed countries. Abstinence from smoking may reduce the risk of AMD in this population.

Age-related macular degeneration (AMD) is one of the common causes of irreversible vision loss among the elderly and is a major risk factor for disability in the older population. It substantially affects the quality of life of an individual. 1 It is estimated that 8 million people will be affected with AMD worldwide by the year 2020. 2 Estimates indicate that 10% to 20% of AMD is the wet form responsible for approximately 90% of severe vision loss. 2 Recent findings from a population-based study from rural India have reported the prevalence of early and late AMD at 2.7% (95% CI, 2.2–3.2) and 0.6% (95% CI, 0.4–0.8), respectively. 3 Treatment options in AMD are limited, and to date there are no established means of reliable prevention of disease progression. 4  
The investigation of risk factors for AMD is important in understanding the disease and suggests preventive measures that can retard or control disease progression. Several studies have reported modifiable and nonmodifiable risk factors for AMD. 5 6 7 8 9 10 11 12 13 14 Although several factors were identified, only age, tobacco smoking, hypertension, and obesity haven been confirmed as increasing the risk of AMD. 5 6 There is also increasing evidence to suggest that cataract surgery is a significant predictor, with a four- and threefold increase in the risk of neovascular AMD and geographic atrophy, respectively. 5 6  
The population attributable risk percentage (PAR%) tells us the percentage of risk in the community that is associated with exposure to a risk factor, and it is used to prioritize public health interventions. 15 16 To the best of our knowledge, although there are reports of the PAR% (13.8% for cigarette smoking) for AMD from Australia, this statistic has not been published for the Indian population. 17 We investigated possible risk factors for AMD and estimated the PAR percentage associated with these risk factors for AMD in a representative sample of the population aged 40 years and more in a state in south India. 
Methods
The details of the design of the Andhra Pradesh Eye Disease Study (APEDS), conducted from 1996 to 2000, in accordance with the tenets of the Helsinki Declaration, have been described previously. 18 19 20 Approval of the Ethics Committee of the Institute was obtained for the study design. 
Briefly, a multistage sampling procedure was used to select the study sample of 10,000 persons, 5,000 each older or younger than 30 years, based on the assumption that a 0.5% prevalence of an eye disease in either of these groups may be of public health significance. This sample would estimate the prevalence as 0.3% to 0.8% at the 95% confidence level. One urban and three rural areas from different parts of the southern Indian state of Andhra Pradesh were selected, with the purpose of including approximately 2500 participants in each area, such that these would roughly reflect the urban–rural and socioeconomic distribution of the population of this state. These four areas were located in Hyderabad (urban), West Godavari district (well-off rural), and Adilabad and Mahabubnagar districts (poor rural). 
For the urban (Hyderabad) component of the APEDS, the blocks (clusters) of Hyderabad were stratified by socioeconomic status and religion. The socioeconomic strata (SES) were extreme lower (monthly per capita income in rupees ≤200 [$US 5:1]), lower (201–500), middle (501–2000), and upper (>2000); the religions were Hindu and Muslim. After this stratification, 24 clusters were chosen by using stratified random sampling, with equal probability of selection, such that the socioeconomic and religious distribution in the sample would be similar to that in the population. The selected clusters were mapped, and households were selected systematically by using a sampling interval of three to five to obtain a similar number of households in the various clusters. A total of 2954 subjects were sampled with the purpose of achieving a recruitment rate of at least 85%, to obtain a minimum sample of 2500. 
From three rural areas from different parts of Andhra Pradesh, 70 rural clusters were selected with the purpose of having a study sample representative of the socioeconomic distribution of the rural population of the state. These three rural areas were located in the West Godavari (well-off rural), Adilabad, and Mahabubnagar (poor rural) districts. For these three rural segments, a total of 8832 subjects were sampled of which 7771 eligible participants were interviewed by trained field investigators. 
The Interview
The participating subjects were interviewed in detail and in a masked manner by the trained field investigators. 19 A structured questionnaire was used to collect the information on risk factors of systemic diseases and personal habits such as smoking. The questionnaire was designed to collect the data on current and prior status of cigarette, beedi, hookah (both are local variants of cigarette), and chutta (home-rolled cigar, prepared and used extensively in the state of Andhra Pradesh) smoking. The first question related to smoking was on the current status of smoking (yes/no). If the response was yes, the volunteer was asked how long he or she had been smoking (years) and the current level (in number per day of cigarettes, beedies, and/or chuttas and in hours per day for the hookah) of smoking. Similar information was also obtained from prior smokers. The structured questionnaire also had questions about alcohol consumption, to ascertain the information on duration, quantity, and frequency of alcohol consumption. Hypertension was deemed to be present if a subject had a history of high blood pressure diagnosed by a physician and/or current usage of antihypertensive medications and/or a blood pressure reading of ≥140/90 mm Hg. Diabetes was deemed to be present if a subject had a history of diabetes and/or diabetic retinopathy on clinical examination. History of duration of diabetes since diagnosis was also documented. 
Ophthalmic Examination
Written informed consent was obtained from each subject before examination. Two ophthalmologists and two optometrists, specifically trained in the study procedures, performed the examinations. Distance and near visual acuity, both presenting and best corrected with refraction, were measured under the standard distance and lighting conditions, by using the logarithm of minimum angle of resolution (logMAR) charts 21 obtained from Australian Vision Charts (Forest Hill, Australia). English alphabet charts were used for literate subjects and E-type charts for illiterate subjects. If visual acuity was worse than 20/20, objective refraction was performed with a streak retinoscope (Heine Optotechnik, Herrsching, Germany) and was followed by assessment of subjective acceptance by the subject. External eye examination, assessment of pupillary reaction, and anterior segment examination with a slit lamp biomicroscope (Haag-Streit, Köniz, Switzerland) were performed. Intraocular pressure was measured with a Goldmann applanation tonometer (Haag-Streit). Gonioscopy was attempted on all subjects with a two-mirror lens (NMR-K; Ocular Instruments, Bellevue, WA), and the angle was graded as open, occludable, or occluded, according to Scheie’s classification based on the extent of visible angle structures. 22 If gonioscopy was not possible for a particular patient, the van Herick technique was used to grade the angle with the slit lamp. 23  
Dilated Ophthalmic Examination.
All subjects had their pupils dilated unless contraindicated due to risk of angle-closure glaucoma. An attempt was made to obtain a pupillary diameter of 8 mm for the lens and posterior segment examination. 19 After the dilation, the size of the pupil and intraocular pressure were recorded again. The lens was examined under the slit lamp. The nuclear opacity was graded according to the Lens Opacities Classification System III (LOCS III) 24 ; cortical and posterior subcapsular cataracts were graded according to the Wilmer Classification. 25 Interrater reliability was determined between the study principal investigator and the clinicians who were specially trained for slit lamp grading of cataract with LOCS III and Wilmer classifications. 19 Reliability assessment was also performed between the principal investigator and the clinicians at the APEDS clinic for assessment of age-related macular degeneration and diabetic retinopathy. The details of training and other procedures have been reported elsewhere. 19 Those who graded lens status and AMD were masked to the interview data, and the investigators who administered the questionnaire in the field were masked to the clinical findings. If the crystalline (natural) lens was absent, the absence of any lens (aphakia) or the presence of an intraocular lens (pseudophakia) was ascertained and documented. The absence, presence, and clarity of the posterior lens capsule were determined in aphakic and pseudophakic eyes. Subjects who were physically unable to attend the clinic were examined at home with portable equipment. 
Stereo examination of the disc and macula was performed with a 78-D lens; a 20-D lens was used for indirect ophthalmoscopy. Anterior segment disease was photographed with a Nikon camera (Nikon Corporation, Tokyo, Japan) mounted on the slit lamp, and posterior segment disease with a fundus camera (Carl Zeiss Meditec, Inc., Jena, Germany). All photographs were classified according to an international classification and grading system of age-related macular degeneration. 26 The features looked for were hard and soft drusen, changes in the retinal pigment epithelium, geographic atrophy, choroidal neovascular membrane, and disciform scar. Hard drusen were defined as small, round, flat, yellow-white deposits, and soft drusen as large, round yellow-white deposits. The retinal pigment epithelial changes appeared as areas of hyper- or hypopigmentation. Geographic atrophy was defined as a large area of well-demarcated hypopigmented retinal pigment epithelium, often with apparent choroidal vessels. Choroidal neovascular membrane was defined as a green-gray lesion, with or without subretinal hemorrhage or exudate. 27 Any other abnormality detected was also documented. The cases of AMD thus detected were also confirmed by the principal investigator. Whereas age-related macular degeneration was classified as wet (neovascular) or dry (atrophic), they were combined for analysis in the present report. 
Anthropometric Measurements.
Height, weight, and blood pressure of all subjects were measured and documented as part of the study. 
Data Analysis
Smoking Status.
For this analysis, subjects were categorized as never smokers (never smoked), current smokers, and prior smokers (those who had smoked earlier but were not smoking at the time of the study). Current and prior smokers were those who had smoked for a minimum of 1 year. Subjects who had never smoked, or had smoked for less than 1 year were considered to be “never smokers”. 
Cumulative Smoking Dose.
For this analysis, cigarette and cigar smokers were categorized as light and heavy smoker, based on cigarette and cigar pack years. The pack-year was calculated by multiplying the number of packs of cigarettes or cigars smoked per day by the number of years the person has smoked. We used the 25th percentile pack years to categorize cigarette or cigar smokers as light and heavy smokers. 
Body Mass Index.
Body mass index (BMI) was calculated from the measured height and weight according to the formula weight (in kilograms) divided by height (in meters) squared. Categories used included underweight (BMI <20), normal (20 ≤ BMI ≤ 25), overweight (25 < BMI < 30), and obese (BMI ≥30). 28  
Definitions
Cataract.
We defined presence of nuclear cataract (NC) as at least one eye showing nuclear opalescence of grade 3.0 or higher on LOCS III. 29 Cortical cataract (CC) was considered present if at least one eye had a Wilmer grade ≥2. 19 Posterior subcapsular cataract (PSC) was considered present if at least one eye had a Wilmer grade ≥1. 19  
AMD.
We defined AMD based on the published International Classification and grading system. 26  
Blindness and Moderate Visual Impairment.
Blindness was defined as distance visual acuity <20/200 in the better eye or central visual field loss <20° in the better eye. Moderate visual impairment was defined as presenting distance visual acuity <20/40 to <20/200 in the better eye or equivalent visual field loss. 30 Of the total 10,293 examined subjects, data were analyzed for the 3723 (36.2%) subjects who were ≥40 years of age. 
Statistical Analysis
The prevalence of AMD and other estimates in our sample were adjusted for the estimated age and gender distribution of the population in India for the year 2000 (http://www.census.gov). The 95% confidence intervals were calculated by assuming a Poisson distribution 31 for prevalence <1% and normal approximation of binomial distribution for prevalence of 1% or more. The confidence intervals were adjusted for the design effect of the sampling strategy, which was based on the rates in each cluster. 32 Variables of interest were first tested for associations with AMD in bivariate analysis, using the Fisher exact test or χ2 test, as appropriate. Variables associated with AMD (P < 0.25) in bivariate analysis were further tested in a backward, stepwise multivariable logistic regression model adjusting for potential confounders and potential interactions. PAR% for the individual factors identified in the multivariate logistic regression model were calculated for this study by using Levin’s formula. 33 We considered the prevalence of AMD in nonsmokers in this population as the base line risk for this estimation. Statistical analysis was performed on computer (SPSS, ver. 12.0 for Windows; SPSS, Chicago, IL). A two-tailed P < 0.05 was considered statistically significant. 
Results
Study Population
A total of 2522 (85.4%) of 2954 eligible participants from urban Hyderabad and 7771 (88%) of 8832 eligible participants from three rural Andhra Pradesh districts participated in the study. The study population was representative of both the urban and rural population of the state as a whole. In this study the data were analyzed for those ≥40 years of age. Urban residents’ the ages ranged from 40 to 102 years (53.2 ± 10.9; median 50 years); 429 (45.9%) were men. The age for rural residents ranged from 40 to 95 years (54.7 ± 10.4; median, 54 years), and 1322 (47.4%) were men. 
AMD Prevalence and Potential Risk Factors
Either form of AMD (dry or wet) was detected in 71 (1.91%) of 3723 participants aged ≥40 years. The median age of the subjects with AMD was 59.9 (60 ± 10.2) years (range, 40–81). Dry AMD was present in 109 eyes of 67 (1.79%) participants, and wet AMD was present in 7 eyes of 4 (0.11%) participants. Of the 71 subjects with AMD, 9 (12.7%; 95% CI, 4.25–20.45) were blind in the affected eye. AMD was present in 13 (0.9%) subjects 40 to 49 years of age and 44 (3.51%) subjects ≥60 years of age (Table 1) . Seven (9.86%) of 71 subjects with bilateral AMD had undergone bilateral cataract surgery (pseudophakia or aphakia), and 14 (19.72%) had undergone unilateral cataract surgery (pseudophakia or aphakia). Mixed cataract (nuclear, cortical, and posterior subcapsular) was present in 19 (26.76%) of the patients with AMD. 
The overall age-gender-area–adjusted prevalence of AMD was 1.82% (95% CI, 1.39%–2.25%). Tables 1 and 2report the distribution of AMD. Neither gender (P = 0.632) nor education (P = 0.903) was associated with AMD (Table 1) . The potential risk factors evaluated in the bivariate analysis were age, prior cataract surgery (pseudophakia or aphakia), any cataract (nuclear or cortical or posterior subcapsular), history of cigar or cigarette smoking (current or prior), and visual impairment. The results of multivariate analyses for potential risk factors and its associated PAR% estimates are shown in (Table 3)
In a multivariable logistic regression model that adjusted for potential confounders and for interactions between age and cataract, increasing age was significantly associated with AMD (Table 3) . AMD was also associated with the presence of any cataract, a history of prior cataract surgery, and specifically cortical subtype of cataract (Table 3) . After adjusting for potential confounders in a multivariate model that used systolic and diastolic blood pressures as continuous variables, the odds of AMD were 1.01 (95% CI, 1.00–1.03; P = 0.267) for each unit increase in the systolic blood pressure and 1.03 (95% CI, 1.00–1.05; P = 0.069) for each unit increase in the diastolic blood pressure. The prevalence of AMD was significantly higher among prior cigar smokers (adjusted OR = 3.29; 95% CI, 1.42–7.57) and heavy cigar smokers (adjusted OR = 2.36; 95% CI, 1.17–4.71). The odds of the presence of AMD among current and prior cigarette smokers was higher than the never-smoked reference group but was not statistically significant. The prevalence of AMD was significantly less among light alcohol drinkers (adjusted OR = 0.43; 95% CI, 0.21–0.92; Table 3 ). Moderate vision impairment and blindness were associated with AMD in our sample (Table 3) . The PAR% for hypertension and prior cigar smokers was 10% each and for heavy cigar smokers was 14%. 
Discussion
Data from this population-based study demonstrated the expected association between age and AMD. Cigar smoking, cortical cataract, and cataract surgery were also significantly associated with AMD, whereas light alcohol consumption was protective. Based on our results, cigar smoking and possibly hypertension were identified as modifiable risk factors, whereas age, cortical cataract, and cataract surgery were identified as nonmodifiable risk factors. 
Prevalence of AMD
The age-gender-area–adjusted prevalence of AMD in this population was 1.82% (95% CI, 1.39%–2.25%). Our estimate of AMD was similar to that reported in white populations—1.62% in the Rotterdam Eye Study, 34 1.81% in the Blue Mountains Eye Study, 35 and 1.51% in the Beaver Dam Eye Study 36 —but is higher than previously reported from a different state of south India (0.6%). 3 Although true differences between the two south Indian populations is possible, it is more likely that differences in examination techniques for the diagnosis of AMD led to the difference in prevalence. The previous study did not use retinal photographs to document AMD and hence may have underestimated early AMD. The prevalence of late AMD is almost similar in both these south Indian populations. 
Potential Risk Factors Associated with AMD
As reported in other populations worldwide, age was significantly associated with AMD. 7 34 35 37 38 39 When age was entered in the logistic regression model as a covariate, for each unit (a year) of increment of age, there was a 1.05 (95% CI, 1.03–1.07; P < 0.0001) odds ratio of increment of AMD in this population. The odds of AMD were slightly higher in people of lower socioeconomic status; however, this was not statistically significant in a multivariate model that explored interactions among SES, smoking, and alcohol intake. 
There are conflicting reports of an association of hypertension and AMD. We did not find hypertension to be associated with AMD in our sample. 3 8 40 41 42 43 44 45 46 However, we found higher odds of AMD in the hypertensive group. We do not, however, have any evidence that antihypertensive medications lower the risk of AMD. Our study results suggest that persons with moderate or severe hypertension may benefit from periodic retinal examinations, since they are at risk for development of AMD. 
The prevalence of AMD was significantly higher in those with a history of heavy cigar smoking compared with never smokers. Heavy cigar smoking attributed to 14% of the avoidable risk of AMD in this population (Table 3) . We found higher, but not statistically significant, odds of AMD in cigarette smokers. It is possible that the difference between cigar and cigarette smokers may be associated with differences in the nicotine content and dose inhaled. It is also possible that the nicotine content of home-rolled cigars may be higher, as it uses crude unprocessed tobacco compared with cigarettes and may have more toxicity than the cigarettes. Also, cigars weigh 2 to 3 g each, whereas the cigarettes weigh approximately 0.82 g each. In addition, many cigarettes have filters, whereas the local cigars do not have any. Smoking is the most consistent risk factor associated with the prevalence of AMD. 10 14 17 There are other health benefits that may accrue from not smoking. We did not try to determine effects of passive smoking in this population. 
Our results suggest that the presence of cortical cataract and prior cataract surgery was significantly associated with the increased risk of AMD. The finding of a higher prevalence of AMD in the presence of cortical cataract is not consistent with a previously published report. 47 The significant association of AMD with prior cataract surgery is also not consistent with some of the previously published reports. 5 6 48 49 50 51 Our cross-sectional study design does not allow us to assign causality and it is possible that some of the eyes with prior cataract surgery actually had AMD before the cataract surgery. As suggested earlier, 52 we emphasize that when cataract surgery is indicated in an eye with both early and moderate to severe AMD, the surgeon should discuss the possibility of progression of AMD with the subject. As India has a large cataract burden, this problem should receive great attention for the timely detection and appropriate management of AMD. 
Consistent with the existing literature, we did not find an association between AMD and education or BMI. 17 36 42 53 54 55 Our study results showed an inverse relationship between light alcohol consumption and prevalence of AMD. Given the small sample, it is difficult to make a definite inference, but the finding is similar to that in a previously published report. 56  
The PAR% for associated risk factors varied between 10% and 14%, which suggests that eliminating these factors as a public health intervention may not be priority. However, even if this PAR% is relatively low, there are other potential individual and public health benefits that may accrue from not smoking. Modification of these risk factors assumes greater importance if viewed within the context of greater health benefits not necessarily limited to AMD. Primary care physicians who are made aware of these risk factors may play an important role in referring their patients to an ophthalmologist. 57 Unless we find preventable and/or modifiable risk factors, application of currently accepted clinical care, including laser treatment, 58 photodynamic therapy, 59 submacular surgery, and visual rehabilitation measures, 60 could help affected persons to live more independently until we discover a more effective therapy. 
The strengths of this study are the representativeness of the sample population, the high response rate, and the standardized protocol, including photographic documentation. Limitations include the relatively few cases of AMD. This decreases the power of the study to identify all significant risk factors. 
 
Table 1.
 
Associations between Prevalence of AMD, Demographic Factors, and Vision Impairment in the Study Population
Table 1.
 
Associations between Prevalence of AMD, Demographic Factors, and Vision Impairment in the Study Population
Characteristics Total Population (N = 3723) AMD n (%) P
Age
 40–49 1424 13 (0.9) <0.0001*
 50–59 1047 14 (1.3)
 60–69 899 31 (3.4)
 70+ 353 13 (3.7)
Sex
 Male 1751 31 (1.8) 0.632, †
 Female 1972 40 (2.0)
Socioeconomic status, ‡
 Extreme lower 417 4 (1.0) 0.103*
 Lower 1791 43 (2.4)
 Middle 1317 19 (1.4)
 Upper 145 2 (1.4)
Education
 Illiterate 2200 43 (2.0) 0.903, †
 Literate 1517 28 (1.8)
Place of residence
 Urban 934 19 (2.0) 0.782, †
 Rural 2789 52 (1.9)
Vision impairment
 Normal 2659 25 (0.9) <0.0001*
 MVI 818 36 (4.4)
 Blind 246 10 (4.1)
Table 2.
 
Associations between Prevalence of AMD and Potential Risk Factors
Table 2.
 
Associations between Prevalence of AMD and Potential Risk Factors
Characteristics Total Population (N = 3723) AMD n (%) P
High blood pressure
 No 1910 29 (1.5) 0.150*
 Yes 1813 41 (2.3)
Diabetes
 No 3528 70 (2.0) 0.182*
 Yes 194 1 (0.5)
Nuclear cataract
 No 2661 32 (1.2) <0.0001*
 Yes 895 29 (3.2)
Cortical cataract
 No 3022 39 (1.3) <0.0001*
 Yes 526 21 (4.0)
Posterior subcapsular cataract
 No 3002 46 (1.5) 0.071*
 Yes 548 15 (2.7)
Prior cataract surgery, †
 No 3447 50 (1.5) <0.0001*
 Yes 276 21 (7.6)
BMI
 Normal 1293 26 (2.0) 0.078, ‡
 Underweight 1816 37 (2.0)
 Overweight 312
 Obese 153 4 (2.6)
Cigarette smoking
 Never a smoker 3419 64 (1.9) 0.866, ‡
 Current smoker 179 4 (2.2)
 Prior smoker 125 3 (2.4)
Cigar smoking
 Never a smokers 3224 53 (1.6) 0.001, ‡
 Current smoker 362 10 (2.8)
 Prior smoker 137 8 (5.8)
Beedi smoking
 Never a smoker 3002 63 (2.1) 0.214, ‡
 Current smoker 570 6 (1.1)
 Prior smoker 151 2 (1.3)
Hooka smoking
 Never a smoker 3720 71 (1.9) 1.000*
 Prior smoker 3
More than one form of smoking
 Never a smoker 2347 42 (1.8) 0.737, ‡
 Only one type 1259 26 (2.1)
 More than one type 117 3 (2.6)
Alcohol consumption, §
 Never a drinker 2658 61 (2.3) 0.023, ‡
 Light drinker 805 8 (1.0)
 Heavy drinker 260 2 (0.8)
Table 3.
 
Multivariable Logistic Regression Analyses for Associations between Potential Risk Factors and AMD (n = 3,723)
Table 3.
 
Multivariable Logistic Regression Analyses for Associations between Potential Risk Factors and AMD (n = 3,723)
Characteristics Total Population AMD n (%) Adjusted Odds Ratio (95% CI) PAR*
Age, †
 40–49 1424 13 (0.9) 1.00
 50–59 1047 14 (1.3) 2.04 (0.92–4.60)
 60–69 899 31 (3.4) 4.38 (2.50–7.64)
 ≥70 353 13 (3.7) 3.29 (1.57–7.01)
Vision impairment
 Normal 2659 25 (0.9) 1.00
 MVI 818 36 (4.4) 3.02 (1.68–5.41)
 Blind 246 10 (4.1) 2.89 (1.27–6.55)
High blood pressure, †
 No 1910 29 (1.5) 1.00
 Yes 1813 41 (2.3) 1.25 (0.67–2.29) 0.10 (0.0–0.31)
Any cataract, ‡
 No 2271 22 (1.0) 1.00
 Yes 1442 49 (3.4) 2.29 (1.24–4.29)
Nuclear cataract, §
 No 2661 32 (1.2) 1.00
 Yes 895 29 (3.2) 1.58 (0.84–2.97)
Cortical cataract, §
 No 3022 39 (1.3) 1.00
 Yes 526 21 (4.0) 2.87 (1.57–5.26)
PSC cataract, §
 No 3002 46 (1.5) 1.00
 Yes 548 15 (2.7) 1.12 (0.58–2.19)
Prior cataract surgery, ∥
 No 3447 50 (1.5) 1.00
 Yes 276 21 (7.6) 3.79 (2.12–6.78)
History of smoking
 Cigarette smoking
  Never a smoker 3419 64 (1.9) 1.00
  Current smoker 179 4 (2.2) 1.65 (0.55–5.01) 0.03 (0.0–0.20)
  Prior smoker 125 3 (2.4) 1.17 (0.33–4.14) 0.01 (0.0–0.12)
 Cumulative smoking dose, ¶
  Light smoker 58 2 (3.4) 2.80 (0.59–13.26) 0.03 (0.0–0.20)
  Heavy smoker 246 5 (2.0) 2.01 (0.54–5.01) 0.06 (0.0–0.23)
 Cigar smoking
  Never a smoker 3224 53 (1.6) 1.00
  Current smoker 362 10 (2.8) 1.77 (0.84–3.74) 0.07 (0.0–0.24)
  Prior smoker 137 8 (5.8) 3.29 (1.42–7.57) 0.10 (0.01–0.24)
 Cumulative smoking dose, ¶
  Light smoker 83 2 (2.4) 1.30 (0.29–5.77) 0.01 (0.0–0.13)
  Heavy smoker 416 16 (3.8) 2.36 (1.17–4.71) 0.14 (0.02–0.33)
History of alcohol consumption, #
 Never a drinker 2658 61 (2.3) 1.00
 Light drinker 805 8 (1.0) 0.43 (0.21–0.92) 0.14 (0.02–0.18)
 Heavy drinker 260 2 (0.8) 0.45 (0.11–1.81) 0.04 (0.0–0.05)
The authors thank all the APEDS team—in particular, Lalit and Rakhi Dandona and Catherine McCarty, who designed and conducted the detailed study; Vallam S. Rao for clinical inputs; and all the volunteers who participated. 
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Table 1.
 
Associations between Prevalence of AMD, Demographic Factors, and Vision Impairment in the Study Population
Table 1.
 
Associations between Prevalence of AMD, Demographic Factors, and Vision Impairment in the Study Population
Characteristics Total Population (N = 3723) AMD n (%) P
Age
 40–49 1424 13 (0.9) <0.0001*
 50–59 1047 14 (1.3)
 60–69 899 31 (3.4)
 70+ 353 13 (3.7)
Sex
 Male 1751 31 (1.8) 0.632, †
 Female 1972 40 (2.0)
Socioeconomic status, ‡
 Extreme lower 417 4 (1.0) 0.103*
 Lower 1791 43 (2.4)
 Middle 1317 19 (1.4)
 Upper 145 2 (1.4)
Education
 Illiterate 2200 43 (2.0) 0.903, †
 Literate 1517 28 (1.8)
Place of residence
 Urban 934 19 (2.0) 0.782, †
 Rural 2789 52 (1.9)
Vision impairment
 Normal 2659 25 (0.9) <0.0001*
 MVI 818 36 (4.4)
 Blind 246 10 (4.1)
Table 2.
 
Associations between Prevalence of AMD and Potential Risk Factors
Table 2.
 
Associations between Prevalence of AMD and Potential Risk Factors
Characteristics Total Population (N = 3723) AMD n (%) P
High blood pressure
 No 1910 29 (1.5) 0.150*
 Yes 1813 41 (2.3)
Diabetes
 No 3528 70 (2.0) 0.182*
 Yes 194 1 (0.5)
Nuclear cataract
 No 2661 32 (1.2) <0.0001*
 Yes 895 29 (3.2)
Cortical cataract
 No 3022 39 (1.3) <0.0001*
 Yes 526 21 (4.0)
Posterior subcapsular cataract
 No 3002 46 (1.5) 0.071*
 Yes 548 15 (2.7)
Prior cataract surgery, †
 No 3447 50 (1.5) <0.0001*
 Yes 276 21 (7.6)
BMI
 Normal 1293 26 (2.0) 0.078, ‡
 Underweight 1816 37 (2.0)
 Overweight 312
 Obese 153 4 (2.6)
Cigarette smoking
 Never a smoker 3419 64 (1.9) 0.866, ‡
 Current smoker 179 4 (2.2)
 Prior smoker 125 3 (2.4)
Cigar smoking
 Never a smokers 3224 53 (1.6) 0.001, ‡
 Current smoker 362 10 (2.8)
 Prior smoker 137 8 (5.8)
Beedi smoking
 Never a smoker 3002 63 (2.1) 0.214, ‡
 Current smoker 570 6 (1.1)
 Prior smoker 151 2 (1.3)
Hooka smoking
 Never a smoker 3720 71 (1.9) 1.000*
 Prior smoker 3
More than one form of smoking
 Never a smoker 2347 42 (1.8) 0.737, ‡
 Only one type 1259 26 (2.1)
 More than one type 117 3 (2.6)
Alcohol consumption, §
 Never a drinker 2658 61 (2.3) 0.023, ‡
 Light drinker 805 8 (1.0)
 Heavy drinker 260 2 (0.8)
Table 3.
 
Multivariable Logistic Regression Analyses for Associations between Potential Risk Factors and AMD (n = 3,723)
Table 3.
 
Multivariable Logistic Regression Analyses for Associations between Potential Risk Factors and AMD (n = 3,723)
Characteristics Total Population AMD n (%) Adjusted Odds Ratio (95% CI) PAR*
Age, †
 40–49 1424 13 (0.9) 1.00
 50–59 1047 14 (1.3) 2.04 (0.92–4.60)
 60–69 899 31 (3.4) 4.38 (2.50–7.64)
 ≥70 353 13 (3.7) 3.29 (1.57–7.01)
Vision impairment
 Normal 2659 25 (0.9) 1.00
 MVI 818 36 (4.4) 3.02 (1.68–5.41)
 Blind 246 10 (4.1) 2.89 (1.27–6.55)
High blood pressure, †
 No 1910 29 (1.5) 1.00
 Yes 1813 41 (2.3) 1.25 (0.67–2.29) 0.10 (0.0–0.31)
Any cataract, ‡
 No 2271 22 (1.0) 1.00
 Yes 1442 49 (3.4) 2.29 (1.24–4.29)
Nuclear cataract, §
 No 2661 32 (1.2) 1.00
 Yes 895 29 (3.2) 1.58 (0.84–2.97)
Cortical cataract, §
 No 3022 39 (1.3) 1.00
 Yes 526 21 (4.0) 2.87 (1.57–5.26)
PSC cataract, §
 No 3002 46 (1.5) 1.00
 Yes 548 15 (2.7) 1.12 (0.58–2.19)
Prior cataract surgery, ∥
 No 3447 50 (1.5) 1.00
 Yes 276 21 (7.6) 3.79 (2.12–6.78)
History of smoking
 Cigarette smoking
  Never a smoker 3419 64 (1.9) 1.00
  Current smoker 179 4 (2.2) 1.65 (0.55–5.01) 0.03 (0.0–0.20)
  Prior smoker 125 3 (2.4) 1.17 (0.33–4.14) 0.01 (0.0–0.12)
 Cumulative smoking dose, ¶
  Light smoker 58 2 (3.4) 2.80 (0.59–13.26) 0.03 (0.0–0.20)
  Heavy smoker 246 5 (2.0) 2.01 (0.54–5.01) 0.06 (0.0–0.23)
 Cigar smoking
  Never a smoker 3224 53 (1.6) 1.00
  Current smoker 362 10 (2.8) 1.77 (0.84–3.74) 0.07 (0.0–0.24)
  Prior smoker 137 8 (5.8) 3.29 (1.42–7.57) 0.10 (0.01–0.24)
 Cumulative smoking dose, ¶
  Light smoker 83 2 (2.4) 1.30 (0.29–5.77) 0.01 (0.0–0.13)
  Heavy smoker 416 16 (3.8) 2.36 (1.17–4.71) 0.14 (0.02–0.33)
History of alcohol consumption, #
 Never a drinker 2658 61 (2.3) 1.00
 Light drinker 805 8 (1.0) 0.43 (0.21–0.92) 0.14 (0.02–0.18)
 Heavy drinker 260 2 (0.8) 0.45 (0.11–1.81) 0.04 (0.0–0.05)
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