2 Lecturer in Biostatistics, Dept of Community Medicine, Amrita Institute of Medical sciences, Amrita University, Kochi, Kerala, India
3 Social Worker, Dept of Community Medicine, Amrita Community Health Training Centre, Njarakkal, AmritaUniversity, Kochi, Kerala, India
4 Professor, Chair of Non-Communicable Disease Control &Director of the Centre for Health Equity, Melbourne School of Population and Global Health, University of Melbourne, Australia.
Methodology: The adopted local self administration unit of the Medical College which is also the field practice area with a population of 25,096 was taken for the study. All the households in the area were visited and the details regarding self reported diabetes was collected after obtaining informed consent and analysis done by multivariate logistic regression.
Result: The prevalence of self reported diabetes in this coastal area was found to be low at 7.4%.Type 2 diabetes was also found to occur significantly earlier among the respondents belonging to the below poverty line. Age above 40 years(OR2 95%CI 1.5-2.7,p=.000),marital status(OR1.9 95%CI 1.1-2.1,p=.006)presence of comorbidities(OR635 95%CI 389-969,p=.000),more than 8 years of schooling(OR 0.64 95%CI 0.46-0.86,p=.004),living conditions as represented by presence of household source of drinking water(OR 1.4 95%CI 1.01-1.5) were found to be independent predictors. Though there was increasing trend of diabetes among the forward caste and above poverty line families after backward logistic regression this disappeared leaving behind the proxy of socioeconomic status, household source of drinking water.
Conclusion: Though, the state of Kerala is in an advanced stage of epidemiologic transition, coastal areas are still in the earlier phases of transition with low prevalence of type 2 diabetes mellitus. Higher education and better living conditions are important social determinants of diabetes though further studies are necessary to delineate the impact of economic status and education.
Keywords: Social Determinants; Type2 Diabetes; Coastal Areas
Lifestyle factors are strongly patterned by socioeconomic status [8]. The latency model emphasizes that psychosocial and socio-economic conditions vary early in life and will have a strong impact later in life independent of intervening experience [9]. The landmark UK White hall studies pointed out that 90% of variance in occurrence of metabolic syndrome cannot be accounted for by conventional behavioural risk factors [10].The Commission on Social determinants of diabetes in 2008 also reported that the true upstream drivers of health inequities reside in the social, economic and political environments [11]. As we consider improving diabetes outcomes, social determinants of health and diabetes need consideration [12].
In cardiovascular disease(CVD) ,of which diabetes is a major cause the epidemic struck the more affluent sections of India first, but with the maturing epidemic a reversal of social gradient has been observed with socio-economically disadvantaged groups becoming increasingly vulnerable to CVD [13]. However, not all children and adults living in low socio-economic circumstances have poor health; they are more likely to develop poor physical and emotional outcomes than those living in better circumstances [13].
Studies in Kerala have shown a low prevalence in coastal area and it has been suggested that the prevalence of type 2 diabetes and other cardiovascular risk factors may increasingly be concentrated in the lower socioeconomic groups though cross sectional multilevel analysis based on National family Health survey3 data across India indicates otherwise[5,14]. There is strong social patterning in the incidence of type 2 diabetes and therefore it was decided to look into the prevalence and social determinants of diabetes in a coastal area with high population density in a state in an advanced stage of epidemiologic transition [15].
The mean age of the population was 42.7(16.03) yrs with male and females almost equally distributed at 48.9% and 51% respectively. Among the study population the most vulnerable and marginalised group-Scheduled Caste and Scheduled tribe [18] consisted of 17%.Nearly a half (48.16%) consisted of other backward castes and other eligible communities and only a third (34.75 %) belonged to the socioculturally cum economically forward group. The socioeconomic status as determined by the point poverty index indicated that 7.4% were poor or at risk of poverty whereas according to the ration card which is the determinant of identity, eligibility and entitlement to the public distribution system, less than a third (30.02%)were BPL,5.4% had no cards and the rest were APL. The higher level of BPL may be due to underreporting of income data due to availability of many social assistance measures and the point poverty index indicates the poorest of the poor. As far as living conditions in terms of access to water was concerned only 22.8% had access to a house connection. In this water scarce area a majority of the population (67.8%) were using water from a public tap. Toilet facilities indicated that 82.2% had a proper toilet and 7.9% had toilets which drained into the canals which in turn drained into the sea.
The age range of the population affected by diabetes varied from 22 to 90 years with a mean age of 59.28(11.89) years higher than the study population mean of 42.7(16.03). A marginally higher prevalence of type 2 diabetes was found among women at 7.8% (95% CI6.9 to 8.2), though the gender difference is not statistically significant. Correspondingly, women constituted a slightly larger proportion 53.9% among diabetes as compared to 51.03% among the study population. The prevalence of Diabetes increased with increasing age though the peak prevalence was in a significantly younger age at 50-59 years in the BPL(below poverty line) group and no card group compared to 60-69 years in the APL(above poverty line) group(p< 0.008). The no card group indicates people who have recently migrated into the area and have no ration cards and are a vulnerable (Figure 1).
|
DM(%) |
Total |
OR(95% CI) |
P |
|
Age |
<40 yrs |
69(.97) |
7112 |
1 |
<0.001 |
> 40yrs |
969(13.9) |
6924 |
16.6 (13.4,22.3) |
||
Sex |
Male |
479(6.9) |
6873 |
1 |
0.059 |
Female |
559(7.8) |
7163 |
1.13 (.78,1.8) |
||
Marital status |
Never married |
27(.9) |
2843 |
1 |
<0.001 |
Ever married |
1011(9) |
11193 |
10.35 (7.1,15.3) |
||
Poor |
No |
976(7.5%) |
12996 |
1 |
0.06 |
Yes |
62(5.9%) |
1040 |
0.78(.599,1.017) |
||
Ration card status |
BPL |
251(6%) |
4215 |
1 |
|
No card |
29(3.8%) |
766 |
0.4 (.29,1.23) |
0.43 |
|
APL |
758(8.4%) |
9055 |
0.7(0.59,1.12) |
0.62 |
|
Caste |
SC&ST |
172(7.1) |
2398 |
1 |
|
OBC&OEC |
467(6.9) |
6760 |
0.96(0.84,1.8) |
0.66 |
|
Others |
399(8.1) |
4878 |
1.15(1.01,3.4) |
0.13 |
|
Education |
Illiterate |
55(12.7) |
431 |
1 |
|
Upto 7 yrs of schooling |
447(11.3) |
3924 |
.713(0.6,0.9) |
<0.001 |
|
8-12 yrs of schooling |
452(6.1) |
7344 |
27.7.4 (15.3,40.12) |
0.004 |
|
>12 yrs of schooling |
84(3.5) |
2337 |
56.29. (35.12,65.17) |
0.003 |
|
Addictive habits |
No habit |
890 |
12362 |
1 |
|
Ever smoker |
33 |
368 |
1.2(0.9,1.4) |
0.58 |
|
Ever alcoholic |
52 |
516 |
1.4(1.1,1.7) |
0.05 |
|
Ever smoking and drinking |
63 |
790 |
1.1(0.8,1.3) |
0.538 |
|
Co morbidities |
Absent |
7 |
11026 |
1 |
<0.001 |
Present |
1031 |
3010 |
820 |
||
Living conditions |
|||||
Toilet facilities |
None |
65(4.7) |
1376 |
1 |
|
Inappropriate |
70(6.2) |
1112 |
1.3(0.9,1.5) |
0.58 |
|
Appropriate |
903(7.8) |
11548 |
1.7(1.3-1.9) |
<0.001 |
|
Water source |
Public tap |
605(6.4) |
9524 |
1 |
|
Home connection |
337(10.6) |
3183 |
1.74(1.5-3.8) |
<0.001 |
|
Well &bore well |
67(9) |
748 |
1.45(1.24,3.68) |
0.006 |
|
Rainwater |
29(5) |
581 |
.77(.689,1.23) |
0.19 |
Age(in years) |
OR |
95% CI |
p |
> 40 |
2.1 |
1.54-2.77 |
0.001 |
Marital status |
|||
Ever Married |
1.86 |
1.12-2.1 |
0.006 |
Comorbidities Present |
635 |
389-1727.1 |
<0.001 |
Water source Home connection |
1.4 |
1.01-1.2 |
0.001 |
Education |
|||
8-12yrs |
1.63 |
1.23-2.14 |
0.004 |
>12 yrs |
1.8 |
1.22-2.4 |
0.014 |
The country wide risk factor surveillance study done in the four geographic regions of India found an OR of 3(95%CI1.7-2.7) for those with graduate level education compared to those with no formal schooling [19]. In a study based on the NFHS 3(national Family health survey3 2005-2006) which determined the association between socioeconomic status and self reported diabetes where socioeconomic status was compositely determined by estimating household wealth, education and social caste, an increasing prevalence of diabetes with increasing education was observed [14]. In the same study fully adjusted model household wealth was as a significant factor reported consistently across India for self reported diabetes. In this study a significantly higher prevalence of diabetes has been observed among those with 8-12 yrs of schooling and more than 12 years of schooling similar to other studies [14, 17]. There was increasing prevalence of diabetes across the socioeconomic strata as represented by the ration card possessed, such as 3.8% in the no card holders, 6% among the below poverty line (BPL) card holders to 8.4% in the above poverty line (APL) card holders though this was not significant. Therefore the point poverty index was also taken into account and this also showed a similar picture with the at risk (poor) families having lower prevalence of diabetes at 5.9% compared to 7.5% among those not at risk, though not significant. Complex factors in the physical and social environment affect health [20]. Reflective of the socioeconomic status were the access to own household connection of tap water. In the unadjusted analysis a gradient was observed in the analysis with increasing OR from those using a public tap to those having their own home connection. In the adjusted analysis it has been observed that it is the people with own home connection that have higher rates of prevalence of diabetes.
Those with comorbidities such as hypertension, hypercholesterolemia were found to be an independent predictor of a higher prevalence of diabetes. Similar findings from other parts of Kerala indicate that the co existence of other non communicable diseases amplified the burden of diabetes mellitus with a higher association of diseases like hypercholesterolemia, hypertension and obesity [7].
The limitations of this study are that only self reported diabetes was considered which could be an underestimate of the problem. Though, previous research indicates that there is good agreement between self reported diabetes and medical records in a US population and in India self reported health conditions and social determinants like socioeconomic status have an expected relationship [21,22].
Though Kerala is in an advanced stage of epidemiologic transition, it appears that there are some areas which are still in the earlier phases of transition .Thus; the prevalence of diabetes in this coastal area was low at 7.4%. type 2 diabetes has been found to occur at an earlier age among the poorer people. The overall picture seems to indicate the prevalence of the disease among the well to do as indicated by living conditions and educational status where those with at least 8 years of schooling had a higher risk. However, the study all over India also showed household wealth was the strongest socioeconomic factor suggesting that social and behavioural factors such as sedentariness and increased consumption of calories associated with diabetes in India may be more closely related to increasing wealth than educational status [7,14]. In contrast, in western society’s voluntary leisure time physical activity and a healthier lifestyle are more common among the affluent [23]. Economic status and or education are important social determinants though further studies are necessary to delineate the impact of the two factors differentially or cumulatively.
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