Healthy eating among adults
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1. Main facts and figures
- 54.8% of adults aged 16 and over had 5 or more portions of fruit and vegetables a day (‘5 a day’) in 2017/18
- White British adults were the most likely out of all ethnic groups to eat 5 a day, with 55.9% doing so
- the percentage of adults in the Black, Asian, Chinese, and Mixed ethnic groups who ate 5 a day was lower than the national average
- the percentage of White British and Other White adults eating ‘5 a day’ in 2017/18 was lower than the previous year
- for other ethnic groups, too few adults responded to the survey or the responses were too varied to make reliable generalisations about changes over time
The ethnic categories used in this data
The data has been grouped into 7 broad ethnic categories:
- White British
- White Other
- Other ethnicity
2. By ethnicity over time
Summary of Healthy eating among adults By ethnicity over time Summary
The data for this measure is taken from the Active Lives Survey in 2015/16, 2016/17 and 2017/18.
The survey is carried out on behalf of Sport England by research company IPSOS-MORI.
Respondents to the survey were asked 2 questions about how many portions of fruit and vegetables they eat on a usual day. Respondents were counted as eating 5 portions of fruit and vegetables on a usual day (‘5 a day’) if their responses on the numbers of fruit and vegetables added up to 5 or more.
The survey sample is randomly selected from the Royal Mail’s Postal Address File, which has a very high coverage of private residential addresses. A letter is sent to households inviting up to 2 people per household to take part in the survey, either online or by requesting a paper version of the questionnaire.
A random sampling survey design ensures results are representative of the population. Results are based on responses from a sample of around 198,250 people. Only people aged 16 or older were included.
Results from the Active Lives Survey should not be compared directly with other data about what people eat.
The questions are more simplistic than those used in other sources like the National Diet and Nutrition Survey and the Health Survey for England. For example, the Active Lives Survey measures whole numbers of portions with composite foods (fruit/vegetables used in recipes) not explicitly included. In addition, using online or postal responses (rather than a food diary or face to face interview) is different, and it is not unexpected that different survey methods give different results
The results from the Active Live Survey presented here give higher estimates for the percentage of people consuming 5 or more portions of fruit or vegetables a day than both the National Diet and Nutrition Survey and the Health Survey for England.
Weighting is used to adjust the results of a survey to make them representative of the population and improve their accuracy.
For example, a survey which contains 25% women and 75% men will not accurately reflect the views of the general population, which we know has an even 50/50 split.
Statisticians rebalance or ‘weight’ the survey results to more accurately represent the general population. This helps to make them more reliable.
Data has been weighted to ONS population measures for geography and key demographics.
The confidence intervals for each ethnic group are available if you download the data.
54.8% of adults surveyed in 2017/18 reported eating 5 or more portions of fruit and vegetables on a usual day (‘5 a day’). This is a reliable estimate of the percentage of adults in England who ate 5 a day, but because the Active Lives Survey results are based on a random sample of adults aged 16 or older, it is not possible to be 100% certain of the true percentage.
It’s 95% certain, however, that somewhere between 54.6% and 55.1% of all adults in England ate 5 a day in 2017/18. In statistical terms, this is a 95% confidence interval. This means that if 100 random samples were taken, then 95 times out of 100 the estimate would fall in this range (between the upper and lower confidence interval). But 5 times out of 100 it would fall outside this range.
The smaller the survey sample, the more uncertain the estimate and the wider the confidence interval. For example, the number of people from the Chinese ethnic group sampled for this survey is relatively small compared with the entire population, so we can be less certain about the estimate for the smaller group. This greater uncertainty for people from the Chinese ethnic group is expressed by the wider confidence interval of between 47.0% and 53.6%.
Statistically significant findings have been determined where the 95% confidence intervals of an ethnic group do not overlap when comparing with another ethnic group or between time periods
The Wilson Score method for calculating confidence intervals has been used. This gives very accurate confidence intervals for proportions and odds based on the assumption of a binomial distribution. The Wilson Score method is the preferred method for calculating confidence intervals for proportions.
For further details of the sampling method and weighting see the Active Lives Survey 2017/2018 Year 3 Technical Note (PDF opens in a new window or tab) (PDF).
Figures have been rounded to 1 decimal point in the charts and tables. Unrounded figures are available if you download the data.
4. Data sources
Type of data
Type of statistic
Twice a year
Purpose of data source
The Active Lives Survey measures the number of people aged 16 and over who take part in sport and physical activity.
This data informs the government’s strategy on physical activity, Sporting Future, which looks at 5 aspects of physical activity:
- physical well-being
- mental well-being
- individual development
- social and community development
- economic development
Type of data
Type of statistic
Public Health England
Purpose of data source
The Public Health Outcomes Framework examines indicators that help government, health researchers and practitioners, understand trends in public health.
5. Download the data
Measure, Ethnicity, Ethnicity_Type, Time, Time_Type, Geography, Geography_Type, Geography_Code, Gender, Age, Value, Value_Type, Denominator, Confidence Intervals