Incidence of Visually Impairing Cataracts Among Older Adults in Kenya

Key Points Question How many new people per year become visually impaired from cataract in Kenya? Findings In this secondary analysis of the Nakuru Eye Disease Cohort Study of 4364 participants at baseline and 2159 participants at follow-up, the 6-year cumulative incidence of visually significant cataract in either eye was 251.9 per 1000, with the incidence increasing with age among those aged 50 to 59 years and those 80 years or older. Meaning In Kenya, reducing the burden of sight loss from cataract is a national priority, given its high incidence among older adults; the cataract surgical rate needs to be at the level of the incident rate to prevent the prevalence of blindness and visual impairment from increasing.


Additional ethical considerations
Baseline approval was provided by the Kenya Medical Research Institute Ethics Committee and by the African Medical and Research Foundation (AMREF) Ethics Committee, Kenya for the follow-up (AMREF-ESRC P44/12). For both phases approval was granted by the Rift Valley Provincial Medical Officer and the Nakuru District Medical Officer of Health. Approval was sought from the administrative heads in each cluster, usually the village chief. They were also given a copy of the consent form to read and pass on to those in the village.

Retracing at Follow-up -Advance Team
Approximately one week before the follow-up examination clinic was planned for a given cluster, a field officer studied the maps of the village including GPS coordinates recorded at baseline and made phone contact with the village chief or guide to arrange the visit. At the planning visit, a list of study participants were given to the chief and a local village guide was recruited to assist location of the study participants. At this visit the examination site was established and identification of amenities such as electricity, water and road access were made. Two days prior to the clinic, the field officer reminded chiefs of the visit by phone and notified them and the guide of the advance team's arrival.
On the day prior to the examination clinic, the Advance Team visited homes of baseline participants and confirmed their identity using National Identity cards and invited them to attend the examination clinic the following day. All identified participants were also asked to help locate baseline participants that had not been found. At baseline, capillary blood was taken from all participants for random blood glucose, in addition at follow-up glycosylated haemoglobin was taken in all with a self-reported history of diabetes, or random blood glucose of ≥7.0mmol/L and a further 10% of non-diabetics (based on history and random blood glucose).

Interview
An interviewer performed a structured interview in the participant's preferred language covering i) demographic details including; name, year of birth, ethnicity and education level; ii) past medical and ocular history including medical or ophthalmic medication or surgery and relevant family history; iii) known risk factors, including smoking and tobacco consumption and alcohol intake; iv) socioeconomic status based on job, housing conditions, ownership of material goods and livestock which is translated in to a score based on previous work in the same population. 17

Visual Acuity Definitions
WHO definitions of visual impairment and blindness were used throughout 19 . Monocular visual impairment is defined as visual acuity <6/18 (20/60) in either eye. Visual impairment is ©2019 Bastawrous A et al. JAMA Network Open defined as a visual acuity of <6/18 in the better eye. Monocular blindness was defined as a visual acuity of <3/60 (20/400) in either eye. A person was considered to be blind if the visual acuity in the better eye was <3/60. The definition of visual impairment also includes those who were blind.

Extrapolation of data
Estimates of cumulative incidence were extrapolated to estimate the number of adults over the age of 50 with incident visual impairment or blindness in Kenya. This was calculated by taking 2015 population estimate from Kenya (Census Bureau of Kenya) by age category and gender and multiplying this by the age and gender specific estimates of annual cumulative