| Literature DB >> 30908526 |
Lizzie Caperon1, Abriti Arjyal2, Puja K C2, Jyoti Kuikel2, James Newell1, Remco Peters1, Andrew Prestwich3, Rebecca King1.
Abstract
Instances of non-communicable diseases such as diabetes are on the rise globally leading to greater morbidity and mortality, with the greatest burden in low and middle income countries [LMIC]. A major contributing factor to diabetes is unhealthy dietary behaviour. We conducted 38 semi structured interviews with patients, health professionals, policy-makers and researchers in Kathmandu, Nepal, to better understand the determinants of dietary behaviour amongst patients with diabetes and high blood glucose levels. We created a social ecological model which is specific to socio-cultural context with our findings with the aim of informing culturally appropriate dietary behaviour interventions for improving dietary behaviour. Our findings show that the most influential determinants of dietary behaviour include cultural practices (gender roles relating to cooking), social support (from family and friends), the political and physical environment (political will, healthy food availability) and individuals' motivations and capabilities. Using these most influential determinants, we suggest potentially effective dietary interventions that could be implemented by policy makers. Our findings emphasise the importance of considering socio-cultural context in developing interventions and challenges one-size-fits-all approaches which are often encouraged by global guidelines. We demonstrate how multifaceted and multi layered models of behavioural influence can be used to develop policy and practice with the aim of reducing mortality and morbidity from diabetes.Entities:
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Year: 2019 PMID: 30908526 PMCID: PMC6433239 DOI: 10.1371/journal.pone.0214142
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Characteristics of patients who participated in individual patient interviews (May–June 2017).
| ID | Age | Gender | Partner (P) or single (S) interview | Income group | Ethnicity | Religion | Diagnosis | Time since diagnosis | Number of people in household |
|---|---|---|---|---|---|---|---|---|---|
| 35 | 51 | F | S | Rs. 50,000–75,000 | Chhetry | Hindu | Diabetes | 9 years | 4 |
| 34 | 55 | F | S | Less than Rs. 50,000 | Sherpa | Buddhist | Diabetes | 5 years | 5 |
| 45 | 52 | M | P | 75,000–100,000 | Brahmin | Hindu | Diabetes | 2 years | 5 |
| 44 | 33 | M | S | 50,000–75,000 | Chhetry | Hindu | Diabetes | 4 years | 3 |
| 46 | 60 | F | S | 50,000–75,000 | Brahmin | Christian | HBGLs | 14 years | 4 |
| 38 | 54 | F | S | More than 1,00,000 | Magar | Hindu | HBGLs | 1 year | 5 |
| 33 | 59 | F | P | less than Rs. 50,000 | Newar | Hindu | Diabetes | 1.5 years | 4 |
| 32 | 62 | F | P | less than Rs. 50,000 | Brahmin | Hindu | Diabetes | 12 years | 3 |
| 26 | 45 | M | S | 50,000–75,000 | Chhetry | Hindu | Diabetes | 5 years | 4 |
| 68 | 51 | M | S | More than 1,00,000 | Brahmin | Hindu | HBGLs | 2 months | 3 |
| 73 | 38 | F | S | More than 1,00,000 | Brahmin | Hindu | Diabetes | 4 years | 5 |
| 75 | 35 | F | S | less than Rs. 50,000 | Chhetry | Hindu | Diabetes | 11 years | 5 |
| 1 | 46 | M | S | Less than 50,000 NRs | Newar | Hindu | Diabetes | 9 month | 5 |
| 6 | 39 | F | S | 50,000–75,000 NRs | Chettri | Hindu | Diabetes | 10 years | 7 |
| 10 | 55 | M | S | Less than 50,000 NRs | Rai | Hindu | Diabetes | 9 years | 6 |
| 8 | 49 | M | P | Less than 50,000 NRs | Chettri | Hindu | Diabetes | 13 years | 4 |
| 11 | 56 | F | P | Less than 50,000 NRs | Magar | Hindu | Diabetes | 5 years | 5 |
| 12 | 55 | M | P | More than 1,00,000 | Brahmin | Hindu | Diabetes | 7 months | 6 |
| 7 | 63 | M | S | Less than 50,000 NRs | Chettri | Hindu | Diabetes | 8 years | 7 |
| 23 | 52 | F | S | Less than 50,000 NRs | Newar | Hindu | HBGLs | 2 years | 4 |
| 82 | 57 | M | S | More than 1,00,000 | Brahmin | Hindu | HBGLs | 10 months | 4 |
| 83 | 44 | M | S | Less than 50,000 NRs | Chettri | Hindu | HBGLs | 3 months | 5 |
Characteristics of health workers, researchers, senior clinicians and policy makers who participated in individual interviews (May–June 2017).
| ID | Type of Interviewee | Gender | Occupation |
|---|---|---|---|
| 01HW | Health worker | Female | Dietician |
| 02HW | Health worker | Female | Dietician |
| 03HW | Health worker | Female | Dietician |
| 04HW | Health worker | Female | Community health centre worker |
| 05HW | Health worker | Female | Community health centre worker |
| 06HW | Health worker | Female | Community health centre worker |
| 07HW | Health worker | Female | Clinician |
| 08HW | Health worker | Male | Clinician |
| 09HW | Health worker | Male | Community health leader |
| 01SH | Senior clinician | Male | Clinician |
| 02SH | Researcher | Female | Researcher |
| 03SH | Senior clinician | Female | Clinician |
| 04SH | Policy-maker | Male | Government official |
| 05SH | Policy-maker | Female | Government official |
| 06SH | Researcher | Male | Researcher |
| 07SH | Researcher | Male | Researcher |
Levels of themes emerging from the analysis.
| Level of influence | Theme | Sub-code (where appropriate) | Code of specific influencing factor |
|---|---|---|---|
| Personal psychological capabilities | Individual capacity for motivation | ||
| Individual capacity for change | |||
| Access to ‘outside’ food and fast food | |||
| Consumption of food in the home | |||
| Availability of healthy food and junk food | |||
| Government campaigns and policy | |||
| Political will | |||
| Cultural practices | Culturally appropriate food | ||
| Ethnic dietary practices | |||
| Religious dietary practices, festivals and fasting rituals | |||
| Social support | Support from family (household), friends, community | ||
| Gender constructs | Socio-culturally constructed gender roles | ||
| Female/male involvement in food and cooking | |||
Fig 1Ecological Model of determinants of dietary behaviour in patients with diabetes and HBGLs in Kathmandu.