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Background: In recent decades, Sri Lanka has experienced rapid urbanization, with approximately 30% of the population currently residing in urban areas. We report the age- and sex-specific prevalence of dysglycaemia in an urban population in Colombo, Sri Lanka. Methods: Using a stratified random sampling method, 463 subjects (139 men; 324 women) aged 18 years and above were included. Physical activity was quantified using international physical activity questionnaire (IPAQ). Bio impedence was used to estimate body fat. Insulin sensitivity was estimated using the HOMA calculations. Prevalence was estimated using weighted age standardized calculations. Multiple logistic regression analyses were used to study associations to diabetes and prediabetes. Results: There were 124 adults in the 18-40 age group (70% female), 209 adults in the 41-60 age group (73% female) and 130 adults in the > 60 age group (63% female). The overall prevalence of diabetes was 27.6% (95% CI: 23.7-31.4). The prevalence of diabetes in those aged 18-40 was 12.4% (95% CI: 6.4 -18.4), 36.1% (95% CI: 29.8 – 42.4) in those aged 41 – 60 and 48.3% (95% CI: 40.7 – 55.8) in those aged >60. Pre-diabetes was detected in 30.3% (95% CI 25.9-34.8) of the population (with either an HbA1c of 5.7-6.4%, FPG of 110-125 mg/dl or 2 Hr PPG of 140-199 mg/dl). Cumulative prevalence of diabetes and pre-diabetes in the population was 57.9%. Conclusions: This urban study demonstrates that along with the changes in the socio-demographic status, the metabolic profile of the Sri Lankan adult has transformed, with a high prevalence of dysglycaemia and obesity.
Original Article
High prevalence of Diabetes Mellitus in Sri Lankan urban population
Data from Colombo Urban Study.
N. P. Somasundaram1, I. Ranathunga1, K. Gunawardana1, D. S. Ediriweera2
1Diabetes and Endocrine Unit, National Hospital of Sri Lanka, Colombo
2Biostatistics and Epidemiology, Faculty of Medicine, University of Kelaniya, Sri Lanka
Copyright: This is an open-access article distributed under the terms of the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original
author and source are credited (CC BY 4.0)
Correspondence: e-mail< >.
In recent decades, Sri Lanka has experienced rapid urbanization, with approximately 30% of the population currently residing
in urban areas. We report the age- and sex-specific prevalence of dysglycaemia in an urban population in Colombo, Sri Lanka.
Using a stratified random sampling method, 463 subjects (139 men; 324 women) aged 18 years and above were included.
Physical activity was quantified using international physical activity questionnaire (IPAQ). Bio impedence was used to estimate
body fat. Insulin sensitivity was estimated using the HOMA calculations. Prevalence was estimated using weighted age
standardized calculations. Multiple logistic regression analyses were used to study associations to diabetes and prediabetes.
There were 124 adults in the 18-40 age group (70% female), 209 adults in the 41-60 age group (73% female) and 130 adults
in the > 60 age group (63% female). The overall prevalence of diabetes was 27.6% (95% CI: 23.7-31.4). The prevalence of
diabetes in those aged 18-40 was 12.4% (95% CI: 6.4 -18.4), 36.1% (95% CI: 29.8 42.4) in those aged 41 60 and 48.3%
(95% CI: 40.7 55.8) in those aged >60. Pre-diabetes was detected in 30.3% (95% CI 25.9-34.8) of the population (with either
an HbA1c of 5.7-6.4%, FPG of 110-125 mg/dl or 2 Hr PPG of 140-199 mg/dl). Cumulative prevalence of diabetes and pre-
diabetes in the population was 57.9%.
This urban study demonstrates that along with the changes in the socio-demographic status, the metabolic profile of the Sri
Lankan adult has transformed, with a high prevalence of dysglycaemia and obesity.
Sri Lanka, a middle-income country in Asia with a
population of 20 million, has been experiencing rapid and
unplanned urbanization over the recent decades with an
estimated 30% of the population now living in urban and
suburban areas (1). The urban prevalence of Diabetes,
prediabetes and obesity has been rising exponentially
over the past three decades. A study in subjects aged over
20 years indicated a population prevalence of
dysglycaemia (defined as T2DM or IGT or IFG) of
21.8%, which rose to 30% in urban areas (2). Metabolic
syndrome was found in 27.1% of urban adults (3). Physical
inactivity, elevated body mass index (BMI) and central
obesity along with living in an urban area are thought to
be strongly associated with the increased risk of
The study population consisted of adult males and
females who were 18 years and above, whose permanent
residence was in the Eastern Kuppiyawaththa local
government (Grama-Niladhari) division of the Colombo
District. The sample represents an urban population
living in Colombo. This local government area was
selected for the community cohort as it is the closest to
the National Hospital of Sri Lanka, which is the main
research center. The study was carried out in 2014/2015.
Sample size
Sample size was calculated using the Lwanga and
Lameshow 1991 formula of n = z2 p (100-p)D/ d2.
Sample size of 600 was arrived at for expected prevalence
of dysglycaemia and obesity of 50%, design effect of 1.2
with a precision of 95% and an anticipated 25% non-
response rate using the EPI 6 sample calculation
Sampling technique
Stratified simple random sampling was used to select a
sample of 463 from the total population of 6473 in the
GN area registered in who belonged in the age categories
of 18-40 years, 40-60 years and above 60 years. People
who are included in the voters list of Colombo district or
lives in Colombo district continuously for at least three
years were included in the sampling process. In order to
ensure the precision of the estimates in the subsample
analysis (according to the age groups) the sample was
divided among the 3 age categories on a weighted basis
that took into account the proportion in the population
and the expected prevalence of dysglycaemia.
Using a random number generator, study subjects were
randomly allocated into the three strata as follows. In the
18-40 age stratum 210 were selected (35% of total
sample) whilst in the 40-60 years stratum 240 were
selected (40% of the sample) and in the above 60 year
stratum 150 were selected (25% of the sample). The
resulting disproportionate sample allocation was
accounted for, by the use of weighted analysis. The
weights were the inversion of the sampling fractions in
the analysis.
Data collection
The participants were recruited at their homes by a team
of researchers who provided an invitation letter and
information documents. On the day of the screening,
informed written consent was taken and data was
collected using an interviewer-administered
questionnaire administered by trained interviewers, to
collect data including socio-demographic data, use of
alcohol, smoking, food frequency and physical activity,
and detailed medical history on previous diagnoses and
treatment. Anthropometric measurements were made
(weight, height, waist circumference, total body fat
estimation and visceral fat percentage using a bio
impedance analyzer- OMRON HBF 516). Blood samples
were taken in a nine to twelve hours fasting stage and in
non-diabetics 75g anhydrous glucose was given and
blood was collected for glucose measurement two hours
later. Plasma Glucose (GOD- PAP5 method, Olympus
AU 480/680/400 analyser), cholesterol (CHOD-PAP
method, Olympus AU 480/680/400 analyser),
triglyceride (GPO-PAP method, Olympus AU
480/680/400 analyser), glycosylated hemoglobin (HPLC
method, Bio-Rad Variant II Turbo analyser), serum
insulin (Chemiluminescent enzyme immunoassay,
Immulite 1000 analyser), corrected calcium (Arzenso III
method, Olympus AU 480/680/400 analyser) and 25-
OH Vitamin D level (Direct Chemiluminescence
method, Advia centaur analyser) were measured in the
blood samples. Once the serum insulin levels were
analyzed, insulin resistance and beta cell function were
calculated using the HOMA calculator (4).Diabetes
mellitus was diagnosed based on the ADA/WHO
criteria. This required either a documented prior
diagnosis of diabetes or a value above the diagnostic
threshold on biochemical testing. The cutoffs included a
FPG above 126mg/dl, 2 Hour PPG above 200 mg/dl, or
HBA1C above 6.5%. Pre-diabetes was diagnosed with
any of the following values: FPG of 110-125 mg/dl or 2
Hour PPG of 140-199 or an A1C of % 5.7-6.4%.
Statistical analysis:
Data analysis was performed in the R programming
language version 3.2.2 (5). Community based prevalence
rates and means with 95% confidence intervals for the
urban study population and for different strata including
age and gender were calculated considering the stratified
sampling methodology using the “Survey” package in the
R programming language (5). Age adjusted prevalence
rates were calculated based on direct standardization
method using the World Health Organization world
standard population. Descriptive data analysis was
carried out to describe study population characteristics.
Exploratory data analysis was done to identify the risk
factors associated with diabetes mellitus. Exposure
variables studied were age, gender, ethnicity, education
level, smoking habits, alcohol consuming habits, family
history of diabetes, hypertension and hyperlipidemia,
past medical history of diabetes, hypertension and
hyperlipidaemia, weight, height, body mass index (BMI),
waist circumference, neck circumference, body fat
percentage, visceral fat percentage, physical activity
which was quantified as metabolic equivalent of tasks
(METS minutes per week) based on International
Physical Activity questionnaire (6), food habits based on
one week food recall in the Food Frequency
Questionnaire and vitamin D levels. Initially, each study
variable was screened with Pearson’s Chi-square test and
simple logistic regression, and the variables significant at
P =0.2 level were subsequently used for multiple variable
analysis. Subsequently, multiple logistic regression was
carried out to investigate the factors associated with
diabetes status and stepwise selection method was
adopted to select significant variables. Ethnicity
consisted of 4 categories (i.e. Sinhalese, Tamils, Moors
and other), the “other” ethnicity had only 4 individuals
and this group was not considered in the analysis. P value
of 0.05 was considered as significant.
Ethical Issues:
Ethical approval was obtained from the Ethical Review
committee of the Faculty of Medicine, University of
Colombo. Documents were encoded to avoid any
identifying character and measurements were taken to
ensure confidentiality.
A total of 463 subjects gave informed consent and
completed the screening. Most of the respondents were
females (69%). There were 124 subjects in the 18-40 age
group and 70% of these were females. There were 209
subjects in the 41-60 age group and 73% of this stratum
were females. In the over 60-year age stratum there were
130 subjects and 63% were females. The response rate in
each of the above strata was 59%, 87%, and 87% with an
overall response rate of 77.2%. Table 1 summarizes the
basic characteristics of this study population.
This study population’s mean Body mass index was 25.2
kg/m2 (SD 4.8), mean waist circumference was 87.0 cm
(SD 13.0), mean neck circumference was 34.8 cm (SD
3.7), mean total body fat percentage estimated with bio
impedance analysis was 34.3 % (SD 8.3) and the
estimated visceral fat was 9.2% (SD 5.0). Body mass
index was categorized according to global criteria and the
recommended Asian and South Asian criteria (7, 8). 68.2%
of the women and 59.1% of the men were overweight or
obese based on South Asian criteria. The BMI
categorization and distribution are tabulated in Table 2.
Community prevalence for abdominal obesity was 58.1%
based on International Diabetes Federation cut-off
values on waist circumference for determining
abdominal obesity in South Asians (WC male >=
90cm, female >=80cm) (9).
Prevalence of DM and Pre-diabetes
Estimated community mean fasting plasma glucose level
was 101.3 mg/dL (95% CI: 97.6 105.3), HBA1C level
was 6.3% (6.1 6.4) and 2 hour PPG in non-diabetic
individuals was 124 (119.7 129.2). It is notable that
these are relatively high and the mean HBA1C is in the
prediabetes range. These are tabulated in table 3. Family
history of Diabetes Mellitus in at least one first degree
relative was reported in 43.2 % (95% CI 38.4-48.2) of the
study population and 16.9% (95% CI 13.7-20.1) had
previously been diagnosed to have diabetes mellitus.
Estimated community prevalence of diabetes mellitus
was 27.6% (95% CI 23.7-31.4) and prediabetes was seen
in 30.3% (95% CI 25.9-34.8) of the population. Age
adjusted community prevalence of diabetes was 27.1%
and prediabetes was 30.1%. The community prevalence
of dysglycemia was 57.9%; this was seen in 36.2 % in the
18-40 age stratum, in 70.7% in the 41-60 stratum, and in
83.5% in the over 60 stratum. Thus, population
prevalence with normoglycaemia declined from 63.8% in
the 18-40 age stratum to 29.3% in the 41-60 age stratum
to 16.5% in the over 60 age stratum (Table 4).
Among ethnic groups, Moors had the highest prevalence
of Diabetes Mellitus of 36.1% (95%CI 25.5-46.7)
followed by Sinhalaese (30%, 95% CI 22.4-31.6) and
Tamils (19.4, 95% CI 8.8-29.9). Those with the lowest
educational background had the highest prevalence of
diabetes (39.1% (95% CI 28.2-50). Current tobacco
smokers had higher prevalence of diabetes mellitus
(50.1%, 95% CI 33.4-66.7) compared to those who never
smoked (25.2%, 95% CI 21.4-29.1). Ex consumers of
alcohol had the highest prevalence of diabetes mellitus
(52.9%, 95% CI 31-74.8) compared to non-consumers of
alcohol or current consumers (Table 5).
Hundred and two subjects (16.9%) had prior diagnosis of
diabetes mellitus. We further analyzed this subgroup who
were already diagnosed to have diabetes mellitus and
estimated level of control. Mean HbA1C in those who
had prior diagnosis of diabetes mellitus was 8.3% (95%
CI: 7.9 8.8) and mean HOMA ß was 47.6 (95% CI: 33.3
-61.8) indicating declining insulin reserve. HBA1C less
than 7% was found in 29.3% (19.7 38.9%), HBA1C
between 7% and 8 % in 29.5% (20.1. % - 38.8%), and
HBA1C above 8% was found in 41.2% (31.0% 51.5%).
In the population previously diagnosed with diabetes,
blood pressure more than 130/90 mmHg was detected
in 33.4% (95% CI: 24.2 -42.6), LDL cholesterol above
100mg/dl was found in 58.1 (48.9 - 69.0), and triglyceride
above 150mg/dl was found in 41.6% (31.4 51.8).
Explorative analysis
Multiple variable analysis showed increasing age, family
history of diabetes, preexisting hypertension, increasing
BMI, increasing neck circumference, higher frequency of
consuming egg yolk and whole grain and less sweet
consumption had significant associations with diabetes.
Lifestyle factors such as level of physical activity or
amount of sitting time recorded with IPAQ did not
demonstrate any significant association with the presence
of diabetes in the analysis (Table 6).
The incidence and the prevalence of diabetes mellitus is
a rapidly rising in Sri Lanka as well as globally. Urban
population is at a higher risk due to multiple predisposing
factors. This study was done to ascertain the true urban
prevalence of diabetes mellitus as increasing numbers of
diabetic patients living in urban areas are encountered in
clinical settings. There was an alarmingly high prevalence
of dysglycemia in the urban population studied. This is
of enormous clinical and economic significance as even
the younger population in the 18-40 age stratum had a
prevalence of diabetes mellitus of 12.4% and prediabetes
of 24.8% with potential to conversion to diabetes in the
near future. The high prevalence that has been shown in
our study is higher than urban prevalence of 18%
according to Katulanda et al nine years ago (2). It is
possible that the prevalence has actually increased,
however this study used HBA1C in addition to the FPG
and 2 Hour PPG used in the previous study and this may
explain part of the increase in prevalence. A previous
Colombo suburban study that used all three biochemical
parameters reported a prevalence of 20% (10).
Among the factors explored in this study; increasing age,
increasing BMI, increasing neck circumference and
presence of hypertension as well a family history of
diabetes mellitus in a first degree relative, high frequency
of consuming egg yolk, whole grain and less sweet
consumption are significant in multiple regression
analysis. Even though less whole grain consumption and
more sweet consumption are believed to be associated
with diabetes, our results showed the inverse. This need
to be carefully interpreted as already diagnosed diabetics
tend to eat less sweets and more whole grain as a diabetes
control measure. We also found that Vitamin D level was
not significantly associated with diabetes mellitus and the
results will be discussed in detail in another article.
Several key causative factors have not been explored in
this study; they include genetic and epigenetic factors as
well as foetomaternal environment, childhood feeding
and childhood exercise.
We have detected the highest reported prevalence of
diabetes mellitus in the South Asian region and these
prevalence rates are alarming. The existing pool of
patients with diabetes who are likely to develop
significant morbidity over time is a major policy and
health planning concern. The presence of a large number
of individuals who have prediabetes and can develop
diabetes in the future should prompt urgent nationwide
interventions as well as personalized interventions such
as dietary and exercise counselling. We have previously
reviewed possible public health interventions to prevent
diabetes and other non-communicable diseases in South
Asia (11). In light of the current findings, these
interventions may need to be targeted more towards the
above high risk groups in the urban population.
List of abbreviations
BMI - Body mass index
FPG-Fasting Plasma Glucose,
2 Hour PPG- Post prandial Glucose 2 hours
after 75 g glucose
LDL - Low-density lipoprotein cholesterol,
HOMA ß- Homeostasis Model Assessment
estimate of steady state beta cell function
HDL -High-density lipoprotein cholesterol
TG- Triglycerides
HBA1c-Haemoglobin A1c
TSH-Thyroid stimulating hormone,
WHO-World health organization
WC-Waist circumference
Competing interests:
Authors declare no conflict of interest
Ethics approval and consent to participate
Ethical approval was obtained from the Ethical Review
committee of the Faculty of Medicine, University of
Colombo. All participants who enrolled in the study
signed an informed consent form.
Consent for publication
Not applicable.
Availability of data and materials
The data analyzed in this paper can be made available to
researchers. Requests for access to the dataset used in this
paper should be directed to the corresponding author.
Competing interests
None of the authors have any financial or non-financial
competing interests to disclose.
Medical Research Institute, Colombo funded the project
Authors’ contributions
NPS and KG designed the study and were involved in
data collection. NPS, DSE, IR and KG were involved in
statistical analysis, interpretation of data and drafting the
manuscript. All authors read and approved the final
Authors’ information
NPS is a Senior Consultant Endocrinologist at National
Hospital of Sri Lanka. IR is a Senior Registrar in
Endocrinology at National Hospital of Sri Lanka. KG is
Consultant Endocrinologist at National Hospital of Sri
Lanka. DSE is a Lecturer in Medical Informatics at
Faculty of Medicine, University of Kelaniya, Sri Lanka.
Both sexes
Mean age (SD) years
50.4 (14.8)
50.2 (14.3)
Mean height (SD) cm
153.3 (9.1)
152.4 (6.8)
Mean weight (SD) kg
61.5 (12.6)
59.7 (12.0)
Mean BMI (SD) kg/m2
25.2 (4.8)
25.7 (4.8)
Mean waist circumference cm
87.0 (13.0)
86.8 (13.0)
Mean neck circumference cm
34.8 (3.7)
33.0 (3.4)
Mean body fat %
34.3 (8.3)
37.8 (6.1)
Mean visceral fat %
9.2 (5.0)
8.9 (4.7)
320 (69.1%)
212 (66.2%)
56 (12.1%)
44 (13.8%)
83 (17.9%)
60 (18.8%)
4 (0.8%)
4 (1.2%)
Below Grade 5
77 (16.7%)
67 (20.6%)
Up to Ordinary Level
240 (51.9%)
163 (51.1%)
Up to Advanced Level
127 (27.5%)
80 (25.1%)
Above Advanced Level
18 (3.9%)
9 (2.8%)
Tobacco smoking
396 (85.6%)
313 (97.9%)
Global BMI cut offs
Asian BMI cut offs
South Asian BMI cut offs
7.6 (4.9 10)
26.8 (22.4-31.2)
12.7 (9.6-15.9)
52.8 (47.8 57.7)
Table 1. Study group characteristics.
Table 2. Prevalence (%) of underweight, normal weight, over weight and obesity according to Global,
Asian and South Asian BMI categories
Both sexes
101.3 (97.6 105.3)
106.2 (97.1 115.4)
99.6 (95.4 103.7)
OGTT 2 hr*
124.4 (119.7 129.2)
122.9 (113.9 132.0)
125.1 (119.4 130.7)
6.3 (6.1 6.4)
6.4 (6.1 6.7)
6.2 (6.0 6.4)
Plasma Insulin
5.9 ( 5.2 6.7)
5.8 ( 4.9 6.7)
6.0 ( 5.0 7.1)
1.6 ( 1.3 1.8)
1.5 (1.3 1.8)
1.6 (1.2 1.9)
89.7 ( 77.3 102.0)
83.0 (68.9 97.2)
92.7 (75.9 109.4)
Family history of Diabetes
43.2 (38.4 48.2)
45.6 (36.7 54.5)
42.2 (36.3 48.1)
Past medical history of Diabetes
16.9 (13.7 20.1)
18.1 (11.9 24.2)
16.4 (12.6 20.2)
*In non-diabetic individuals
Both sexes
42.1 (37.5 46.8)
30.3 (25.9 34.8)
27.6 (23.7 31.4)
63.8 (54.1 71.6)
24.8 (16.9 32.6)
12.4 (6.4 -18.4)
29.3 (23.3 35.3)
34.6 (28.4 40.9)
36.1 (29.8 42.4)
60 >
16.6 (10.9 22.2)
35.2 (27.9 42.4)
48.3 (40.7 55.8)
40.3 (31.4 49.2)
27.2 (19.5 34.8)
32.5 (24.6 40.4)
61.1 (45.4 76.8)
19.4 (6.7 32.2)
19.4 (6.7 32.2)
25.4 (14.7 36.1)
33.9 (22.3 45.6)
40.7 (28.6 52.7)
60 >
16.7 (6.8 26.5)
33.3 (20.9 45.7)
50.0 (36.8 63.2)
43.0 (37.2 48.7)
31.8 (26.3 37.2)
25.3 (20.8 29.7)
63.6 (53.1 74.2)
27.3 (17.5 37.1)
9.1 (2.8 15.4)
30.8 (23.6 38.0)
34.9 (27.5 42.4)
34.2 (26.8 41.6)
60 >
16.5 (9.6 23.4)
36.1 (27.2 45.0)
47.4 (38.2 56.7)
Table 3. Estimated glycaemic indices (95% CI) for the study population
Table 4. Crude prevalence of diabetes mellitus and pre-diabetes
41.0 (35.2 46.8)
32.0 (26.5 37.5)
30.0 (22.4 31.6)
60.0 (46.7 73.2)
20.7 (10.4 30.9)
19.4 (8.8 - 29.9)
32.3 (20.9 43.7)
31.6 (21.3 41.9)
36.1 (25.5 46.7)
Below Grade 5
26.5 (23.6 45.2)
34.4 (15.2 37.7)
39.1 (28.2 50.0)
Upto Ordinary level
41.2 (25.5 37.9)
31.7 (34.5 47.9)
27.1 (21.5 32.6)
Upto advanced level
46.5 (20.4 37.4)
28.9 (37.1 55.9)
24.6 (17.4 31.9)
Above advanced level
69.5 (0.0 26.6)
10.8 (47.3 91.7)
19.7 (1.6 37.8)
Tobacco smoking
44.0 (39.0 49.0)
30.7 (25.9 35.5)
25.2 (21.4 29.1)
Current smokers
33.0 (17.0 49.0)
16.9 (6.4 27.3)
50.1 (33.4 66.7)
25.7 (6.3 45.1)
45.5 (25.1 65.9)
28.8 (10.9 46.6)
Alcohol consumers
43.9 (38.6 49.1)
30.2 (25.3 35.2)
25.9 (21.7 30.0)
Current consumers
38.6 (25.9 51.3)
31.7 (20.0 - 43.5)
29.7 (19.3 40.0)
Ex- consumers
19.5 (3.7 35.3)
27.6 (10.0 45.2)
52.9 (31.0 74.8)
Std. Error
z value
Family History of Diabetes
Neck circumference
Egg york
Whole grain
Table 6. Significant variables at Multiple variable analysis for the presence of diabetes mellitus
Table 5. Prediabetes, diabetes based on categories of education, ethnicity, tobacco, and alcohol
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... There has been a marked rise in the prevalence of diabetes and other metabolic diseases in Sri Lanka during the past 30 years. For instance, the prevalence of diabetes in the Western Province of Sri Lanka, which was 5.02% in 1990, increased to 6.5% in 2000, 16.4% in 2006 [40], and further rose to 27.6% by 2015 [41]. When conducting the seroprevalence studies in 2003 and 2013, data regarding the height and weight of individuals were also recorded, and the body mass index (BMI) was calculated. ...
... In 2003, 37/575 (6.43%) of the children studied were classified as obese, and this increased to 59/599 (9.85%) by 2013, which was a significant increase (p = 0.03). Therefore, during a period of 10 years, the proportion of obese children has significantly increased, and the prevalence of diabetes among adults had increased from 6.5% in 2000 to 27.6% by 2015 [41]. Such marked increases in obesity and diabetes in the community may have potentially affected the ratio of symptomatic and asymptomatic infections, and, thereby, contributing to the increase in the number of cases. ...
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Background Dengue infections are on the rise in Sri Lanka and are spreading to all areas in the country. Here, we discuss the changes in dengue epidemiology in Sri Lanka in relation to changes in age distribution, changes in seroprevalence rates over time, and possible reasons contributing to such changes. Methods and findings Although the incidence of dengue increased 20-fold from the year 2000 to 2012 and a further 3-fold from 2012 to 2019, this increase is not reflected in a similar increase in the age-stratified seropositivity rates for dengue. For instance, the annual seroconversion rates were 0.76% in 2013 and 0.91% in 2017. The annual seroconversion rates in the 6 to 17 age group were 1.5% per year in 2003, 3.9% in 2013, and 4.1% in 2017. In addition, although a 13-fold increase in dengue was seen in those who were <19 years of age, a 52.4-fold increase was seen in the 40- to 59-year age group. The case fatality rates (CFRs) have similarly changed, with 61.8% of deaths occurring in those <19 years of age in the year 2000, while in 2012 to 2018, the highest CFR were seen in those who were aged 20 to 39 years. Although there has been a marked increase in the number of cases, the vector densities did not change during a 4-year period. The proportion of adult individuals experiencing a secondary dengue infection has also remained between 65% and 75% between the years 2004 and 2018. Conclusions A change in the ratio of symptomatic to asymptomatic infections can give rise to changes in the reported incidence of dengue. In order to take an appropriate policy decision in dengue control activities, it would be important to study the changes in virus serotypes, vector dispersion, and densities. Further, the contribution of the rise in metabolic diseases to an increase in the symptomatic as well as more severe infections due to dengue is explored.
... In addition, majority of the study sample was females, whereas PTB is commoner among males in Sri Lanka [27]. Anyway, the majority of attendees of any public DM clinic in the country would comprise females [43,44]. Hence it could be safely assumed the estimations of this pragmatic study to be realistic, if active screening was to be conducted in real settings. ...
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End TB strategy by the WHO suggest active screening of high-risk populations for tuberculosis (TB) to improve case detection. Present study generates evidence for the effectiveness of screening patients with diabetes mellitus (DM) for Pulmonary TB (PTB). A study was conducted among 4548 systematically recruited patients over 45 years attending DM clinic at the National Hospital of Sri Lanka. The study units followed an algorithm specifying TB symptom and risk factor screening for all, followed by investigations and clinical assessments for those indicated. Bacteriologically confirmed or clinically diagnosed PTB were presented as proportions with 95% CI. Mean (SD) age was 62·5 (29·1) years. Among patients who completed all indicated steps of algorithm, 3500 (76·9%) were investigated and 127 (2·8%) underwent clinical assessment. Proportion of bacteriologically confirmed PTB patients was 0·1% (n = 6,95%CI = 0·0–0·3%). None were detected clinically. Analysis revealed PTB detection rates among males aged ≥60 years with HbA1c ≥ 8 to be 0·4% (n = 2, 95%CI = 0·0–1·4%). The study concludes that active screening for PTB among all DM patients at clinic settings in Sri Lanka, to be non-effective measure to enhance TB case finding. However, the sub-category of diabetic males with uncontrolled diabetics who are over 60 years of age is recommended as an option to consider for active screening for PTB.
What is tear gas? How does tear gas work on human tissue? Health effects of tear gas. First aid Historical context for tear gas use
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Background: One in five adults in Sri Lanka has either diabetes or prediabetes, and one-third of those with diabetes are undiagnosed. Diabetic foot is a debilitating condition affecting up to 50% of patients with both type 1 and type 2 diabetes. The risk of nontraumatic lower limb amputations is 15 times higher in diabetic patients when compared with nondiabetics. Patient education about correct foot care practices is the cornerstone of prevention of diabetic foot disease. Objective: To assess the prevalence of diabetic foot disease, knowledge, and practices about diabetic foot care among diabetic patients. Methods: 334 patients attending the diabetic clinic in Colombo South Teaching Hospital were recruited according to the inclusion and exclusion criteria. Data were collected using 3 questionnaires, and they were filled using the foot examination findings, patients' medical records, and direct interviewing of the patients. Results: The mean age of the patients included in the study was 58.23 ± 10.65 years while the median duration of diabetes was 10.54 ± 7.32 years. 34.1% patients had peripheral neuropathy, and 29.5% had peripheral vascular disease. Diabetic foot disease according to the WHO definition was present only in 23 (6.9%) patients. There was a significant association between peripheral neuropathy and current or past foot ulcer which took more than 2 weeks to heal (p < 0.05). Knowledge about foot care was less among the studied population, and it was associated with poor foot care practices. Presence of diabetic foot and current or past foot ulcer which took more than 2 weeks to heal were significantly associated with the foot care knowledge and practices (p < 0.05). Conclusion: Improvement of patients' knowledge about foot care and their practices have a significant impact on the reduction of diabetic foot disease.
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Cushing syndrome (CS) comprises symptoms and signs associated with prolonged exposure to inappropriately elevated levels of free plasma glucocorticoids. Iatrogenic CS is the most common form. Endogenous CS, may be caused by either excess ACTH secretion or independent adrenal overproduction of cortisol.
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Aims To describe the burden of diabetes mellitus and impaired fasting glucose in middle-aged residents (35–64 years) in an urban area of Sri Lanka. Methods A cross-sectional survey was conducted in the Ragama Medical Officer of Health area, from which 2986 participants (1349 men and 1637 women) were randomly selected from the electoral registry between January and December 2007. The participants underwent a physical examination and had their height, weight, waist and hip circumferences and blood pressure measured by trained personnel. Fasting blood samples were taken for measurement of glucose, HbA1c and lipids. The prevalence of diabetes (fasting plasma glucose > 7 mmol/l) and impaired fasting glycaemia (fasting plasma glucose 5.6–6.9 mmol/l) and major predictors of diabetes in Sri Lanka were estimated from the population-based data. Results Age-adjusted prevalence of diabetes mellitus in this urban population was 20.3% in men and 19.8% in women. Through the present screening, 263 patients with diabetes and 1262 with impaired fasting glucose levels were identified. The prevalence of newly detected diabetes was 35.7% of all patients with diabetes. Among patients with diabetes, only 23.8% were optimally controlled. In the regression models, high BMI, high waist circumference, high blood pressure and hypercholesterolaemia increased the fasting plasma glucose concentration, independent of age, sex and a family history of diabetes. Conclusions Our data demonstrate the heavy burden of diabetes in this urban population. Short- and long-term control strategies are required, not only for optimal therapy among those affected, but also for nationwide primary prevention of diabetes.
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Abstract Metabolic Syndrome (MS) increases the risk for Coronary Artery Disease, stroke and diabetes. MS is twice more common amongst South Asian immigrants in US compared to native Caucasians. There are no nationally representative studies on prevalence of MS from any of the South Asian countries. The present study aims to evaluate the prevalence of MS among Sri Lankan adults and investigates its relationships with socio-demographic, clinical and biochemical parameters. Data on MS and its associated details were obtained from a population-based cross-sectional study conducted between years 2005–2006. MS was defined according to the International Diabetes Federation criteria. A binary logistic regression analysis was performed using the dichotomous variable MS (0 = absent, 1 = present). The independent co-variants were: gender, age category, area of residence, ethnicity, level of education, income and physical activity. Sample size was 4,485 (Response rate–89.7%), 39.5% were males and mean age was 46.1 ± 15.1 years. The crude prevalence of MS was 27.1% (95% CI: 25.8–28.5), and age-adjusted prevalence was 24.3% (95% CI: 23.0–25.6). Prevalence in males and females were 18.4% (95% CI: 16.5–20.3) and 28.3% (95% CI: 26.6–30.0) respectively (p 50,000 (OR:2.1), and physical inactivity (OR:1.6), all significantly increased risk of developing MS. MS is common among Sri Lankan adults affecting nearly one-fourth of the population. Female gender, increasing age, urban living, higher socio-economical status and physical inactivity were important associated factors.
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Physical inactivity is a global concern, but diverse physical activity measures in use prevent international comparisons. The International Physical Activity Questionnaire (IPAQ) was developed as an instrument for cross-national monitoring of physical activity and inactivity. Between 1997 and 1998, an International Consensus Group developed four long and four short forms of the IPAQ instruments (administered by telephone interview or self-administration, with two alternate reference periods, either the "last 7 d" or a "usual week" of recalled physical activity). During 2000, 14 centers from 12 countries collected reliability and/or validity data on at least two of the eight IPAQ instruments. Test-retest repeatability was assessed within the same week. Concurrent (inter-method) validity was assessed at the same administration, and criterion IPAQ validity was assessed against the CSA (now MTI) accelerometer. Spearman's correlation coefficients are reported, based on the total reported physical activity. Overall, the IPAQ questionnaires produced repeatable data (Spearman's rho clustered around 0.8), with comparable data from short and long forms. Criterion validity had a median rho of about 0.30, which was comparable to most other self-report validation studies. The "usual week" and "last 7 d" reference periods performed similarly, and the reliability of telephone administration was similar to the self-administered mode. The IPAQ instruments have acceptable measurement properties, at least as good as other established self-reports. Considering the diverse samples in this study, IPAQ has reasonable measurement properties for monitoring population levels of physical activity among 18- to 65-yr-old adults in diverse settings. The short IPAQ form "last 7 d recall" is recommended for national monitoring and the long form for research requiring more detailed assessment.
As the incidence of noncommunicable diseases such as diabetes continues to rise at an alarming rate in South-East Asia, it is imperative that urgent and population-wide strategies are adopted. The most important contributors to the rise in noncommunicable disease are a rise in mean caloric intake and a decrease in physical activity. The evidence for population-based dietary approaches to counter these factors is reviewed. Several structural and cohesive interdepartmental coordination efforts are required for effective implementation of prevention strategies. Since low- and middle-income countries may lack the frameworks for effective and integrated multi-stakeholder intervention, implementation of population-based dietary and physical-activity approaches may be delayed and may be too late for effective prevention in current at-risk cohorts. Evidence-based strategies to decrease energy intake and increase physical activity are now well established and their urgent adoption by Member States of the World Health Organization South-East Asia Region is essential. In the context of Sri Lanka, for example, it is recommended that the most effective and easy-to-implement interventions would be media campaigns, restrictions on advertisement of unhealthy foods, taxation of unhealthy foods, subsidies for production of healthy foods, and laws on nutrition labelling that introduce colour coding of packaged foods.
To determine the prevalence of diabetes mellitus and pre-diabetes (impaired fasting glucose and impaired glucose tolerance) in adults in Sri Lanka. Projections for the year 2030 and factors associated with diabetes and pre-diabetes are also presented. This cross-sectional study was conducted between 2005 and 2006. A nationally representative sample of 5000 adults aged >or= 18 years was selected by a multi-stage random cluster sampling technique. Fasting plasma glucose was tested in all participants and a 75-g oral glucose tolerance test was performed in non-diabetic subjects. Prevalence was estimated for those > 20 years of age. Response rate was 91% (n = 4532), males 40%, age 46.1 +/- 15.1 years (mean +/- standard deviation). The age-sex standardized prevalence (95% confidence interval) of diabetes for Sri Lankans aged >or= 20 years was 10.3% (9.4-11.2%) [males 9.8% (8.4-11.2%), females 10.9% (9.7-12.1%), P = 0.129). Thirty-six per cent (31.9-40.1%) of all diabetic subjects were previously undiagnosed. Diabetes prevalence was higher in the urban population compared with rural [16.4% (13.8-19.0%) vs. 8.7% (7.8-9.6%); P < 0.001]. The prevalence of overall, urban and rural pre-diabetes was 11.5% (10.5-12.5%), 13.6% (11.2-16.0%) and 11.0% (10.0-12.0%), respectively. Overall, 21.8% (20.5-23.1%) had some form of dysglycaemia. The projected diabetes prevalence for the year 2030 is 13.9%. Those with diabetes and pre-diabetes compared with normal glucose tolerance were older, physically inactive, frequently lived in urban areas and had a family history of diabetes. They had higher body mass index, waist circumference, waist-hip ratio, systolic/diastolic blood pressure, low-density lipoprotein cholesterol and triglycerides. Insulin was prescribed to 4.4% (2.7-6.1%) of all diabetic subjects. One in five adults in Sri Lanka has either diabetes or pre-diabetes and one-third of those with diabetes are undiagnosed.
The steady-state basal plasma glucose and insulin concentrations are determined by their interaction in a feedback loop. A computer-solved model has been used to predict the homeostatic concentrations which arise from varying degrees beta-cell deficiency and insulin resistance. Comparison of a patient's fasting values with the model's predictions allows a quantitative assessment of the contributions of insulin resistance and deficient beta-cell function to the fasting hyperglycaemia (homeostasis model assessment, HOMA). The accuracy and precision of the estimate have been determined by comparison with independent measures of insulin resistance and beta-cell function using hyperglycaemic and euglycaemic clamps and an intravenous glucose tolerance test. The estimate of insulin resistance obtained by homeostasis model assessment correlated with estimates obtained by use of the euglycaemic clamp (Rs = 0.88, p less than 0.0001), the fasting insulin concentration (Rs = 0.81, p less than 0.0001), and the hyperglycaemic clamp, (Rs = 0.69, p less than 0.01). There was no correlation with any aspect of insulin-receptor binding. The estimate of deficient beta-cell function obtained by homeostasis model assessment correlated with that derived using the hyperglycaemic clamp (Rs = 0.61, p less than 0.01) and with the estimate from the intravenous glucose tolerance test (Rs = 0.64, p less than 0.05). The low precision of the estimates from the model (coefficients of variation: 31% for insulin resistance and 32% for beta-cell deficit) limits its use, but the correlation of the model's estimates with patient data accords with the hypothesis that basal glucose and insulin interactions are largely determined by a simple feed back loop.
To establish a unified working diagnostic tool for the metabolic syndrome (MetS) that is convenient to use in clinical practice and that can be used world-wide so that data from different countries can be compared. An additional aim was to highlight areas where more research into the MetS is needed. The International Diabetes Federation (IDF) convened a workshop held 12-14 May 2004 in London, UK. The 21 participants included experts in the fields of diabetes, public health, epidemiology, lipidology, genetics, metabolism, nutrition and cardiology. There were participants from each of the five continents as well as from the World Health Organization (WHO) and the National Cholesterol Education Program-Third Adult Treatment Panel (ATP III). The workshop was sponsored by an educational grant from AstraZeneca Pharmaceuticals. The consensus statement emerged following detailed discussions at the IDF workshop. After the workshop, a writing group produced a consensus statement which was reviewed and approved by all participants. The IDF has produced a new set of criteria for use both epidemiologically and in clinical practice world-wide with the aim of identifying people with the MetS to clarify the nature of the syndrome and to focus therapeutic strategies to reduce the long-term risk of cardiovascular disease. Guidance is included on how to compensate for differences in waist circumference and in regional adipose tissue distribution between different populations. The IDF has also produced recommendations for additional criteria that should be included when studying the MetS for research purposes. Finally, the IDF has identified areas where more studies are currently needed; these include research into the aetiology of the syndrome.
World Health Organization. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies
World Health Organization. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet. 2004; 363:157-63