Abstract
One-in-four 4–5 years and more than one-in-three 10–11 years have excess weight in England.
Aim
To identify characteristics associated with (1) having overweight, obesity and severe obesity at 11 years and (2) rapid weight gain (defined as increasing weight status by one or more body mass index (BMI) categories) between the ages of 4–5 and 10–11 years.
Method
Using National Child Measurement Programme data, BMI at reception (4–5 years) and year 6 (10–11 years) were linked for 15 390 children. Weight categories were identified at both time points using BMI centile classifications.
For each child, the number of BMI categories they crossed between reception and year 6 was identified. Logistic regression models were fitted to explore associations with sociodemographic characteristics of children with excess weight at age 10–11 years and with children experiencing rapid weight gain between reception and year 6.
Results
Overall, 61.9% of children remained in their original weight category; 30% whose weight increased by ≥1 weight categories and 11.7% by ≥2 weight categories. Only 7.8% had decreased ≥1 weight categories and 0.9% had decreased ≥2 weight categories.
Adjusting for other sociodemographic characteristics, girls were less likely than boys to increase ≥2 weight categories between reception and year 6 (OR 0.64; 95% CI 0.58 to 0.71; p<0.001). Compared to white children, Asian and mixed-ethnicity children had higher odds of rapid weight gain. Children with the highest deprivation were over 6 times more likely to increase ≥2 weight categories between reception and year 6 compared with children with the lowest deprivation (OR 6.1; 95% CI 1.92 to 19.10; p<0.01).
Conclusion
Male children, children of Asian and mixed ethnicity and children with high deprivation are at higher risk of rapid weight gain and should be targeted for intervention.
Keywords: Obesity, Adolescent Health
WHAT IS ALREADY KNOWN ON THIS TOPIC
Trajectory studies in children have shown that children who start school with excess weight are at a greater risk of overweight/obesity later in life.
WHAT THIS STUDY ADDS
We conducted a retrospective cohort study using individually linked data to track weight trajectories from ages 4–5 years to 10–11 years.
We identified that boys, children living in the most deprived areas and those of mixed and Asian backgrounds had the greatest risk of rapid weight gain.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
Identifying children at increased risk of rapid weight gain will inform targeted intervention approaches.
Introduction
Obesity is a growing public health problem. The WHO estimates that the prevalence of obesity has tripled since the mid-1970s with more than 650 million people over 18 years estimated to be living with obesity in 2016.1 In that same period, more than 340 million 5–19 years were living with overweight or obesity and in 2020, an estimated 39 million children under 5 years were living with excess weight.1 In England, by the age of 4–5 years, 12% live with overweight and 10% with obesity. This increases to 15% for overweight and 23% for obesity by the age of 10–11 years. Therefore, the middle childhood years represent a key risk period for weight gain and the development of obesity.2
Obesity increases the risk of developing many health conditions in childhood including type 2 diabetes,3 4 liver,5 6 pulmonary, kidney and orthopaedic disorders and has also been associated with poor academic performance.7 Obesity in childhood also carries a high risk of obesity and its long-term health consequences in adulthood.8
Previous studies exploring weight gain across childhood have identified three main weight trajectories9,13: those who have never been overweight, those with early onset of overweight and those with late-onset overweight. Although most children (51%–84%) who were a healthy weight, stayed at a normal healthy weight, a substantial proportion had a higher weight classification in later childhood.
Several of the studies showed that children from white ethnic backgrounds12 14 15 had the most stable weight trajectories. Children who already had overweight/obesity had an increased risk of remaining in or increasing their weight category.16
Some studies have identified boys to have a greater risk of developing overweight/obesity compared with girls1012,14 17 while others found no sex differences.11 16 Deprivation has also been associated with increased risk of weight gain in childhood.16
Thus far, the targets to reduce obesity in children have not been met. Understanding weight trajectories in childhood and identifying the children most at risk of gaining and retaining excess weight during their primary school years may play an important role in informing targeted approaches to address childhood obesity.
Therefore, the aim of this study was to use longitudinal National Child Measurement Programme (NCMP) data that is linked at the individual level to identify the sociodemographic characteristics of children that are associated with a higher weight category at year 6 and characteristics that are associated with an increased risk of transitioning to a higher body mass index (BMI) weight category (defined as rapid weight gain here) between the ages of 4–5 and 10–11 years.
Methods
Study design
This was a longitudinal analysis using the NCMP data for years 2011/2012, 2012/2013, 2017/2018 and 2018/2019.
Participants
In England, childhood overweight and obesity are monitored through the NCMP.18 Each year, reception aged children (4–5 years) and year 6 children (10–11 years) have their heights and weights measured. BMI centiles are calculated using the British 1990 (UK90) growth reference BMI distribution.19 The NCMP uses this UK population-specific growth reference data, rather than international reference data, to ensure consistency and comparability across publications reporting NCMP data.20 NCMP methods have been described elsewhere.21
For this study, NCMP measurements of reception and year 6 pupils in the Birmingham local authority area were used. This area covers a population of 1.1 million and has high ethnic diversity and socioeconomic disadvantage. To examine weight trajectories, data were linked for two cohorts: Reception years in 2011/2012 and 2012/2013 with their year measurements in years 2017/2018 and 2018/2019, respectively. BMI cut-offs used to monitor population prevalence were used, which are defined as20:
Underweight: ≤2nd centile.
Healthy weight:– ≥2nd but <85th centile.
Overweight: ≥85th centile but <95th centile.
Obese: ≥95th centile.
Severely obese: ≥99.6th centile.
SQL Server Management Studio V.18 was used to generate BMI cut-offs, clean and link the data. Data were matched by first and last names, date of birth and sex. Thereafter, data were anonymised prior to the analyses.
Ethnicity data from the year 6 measurement was used where possible, but if data were missing from this measurement, ethnicity recorded at the reception measurement was used. Participants’ postcodes were mapped to deprivation scores using the Index of Multiple Deprivation (IMD), which measures the relative deprivation of small areas in England. For this study, IMD 201922 was used and presented in deciles. For each participant, their year 6 deprivation decile was used in the analysis.
Data packages
All data analysis took place using STATA V.14.1. Reception and year 6 BMI weight category data were summarised using numbers and proportions and cross-tabulated to examine those remaining in the same weight category and those changing weight category.
Logistic regression models were fitted to explore the association between sociodemographic factors and weight categories at year 6, adjusting for weight category at reception. The three models were fitted with outcomes of:
Overweight (including obese and severely obese) vs all other weight categories.
Obese (including severely obese) versus all other weight categories.
Severely obese versus all other weight categories.
Reception BMI weight category, sex, ethnicity and deprivation were included as model covariates.
To explore the sociodemographic factors related to rapid weight gain and weight loss between reception and year 6, logistic regression models were fitted for the following outcomes: children who:
Increased ≥1 wt categories versus all other weight category changes.
Increased ≥2 wt categories versus all other weight category changes.
Decreased ≥1 wt categories versus all other weight category changes.
Decreased ≥2 wt categories versus all other weight category changes.
Included covariates were sex, ethnicity and deprivation.
Significance level was set at p<0.05 and ORs are presented with 95% CIs.
The NCMP is routinely collected data; approval sought and received from Birmingham City Council and Public Health Governance teams for this research.
Results
There were 27 652 reception children who had weight measurements taken in 2011/2012 and 2012/2013. Of those, 15 390 (55.7%) had measurements at year 6 in 2017/2018 and 2018/2019 and had available postcode and ethnicity data. There were similar proportions of males (49.4%) and females (50.6%). 54% and 16% lived in areas in the first and second most deprived deciles, respectively. The largest ethnic categories were white (39.3%) and Asian (38.2%) (table 1).
Table 1. Participants characteristics.
| Characteristics | Participantsn=15 390n (%) | |
| Male | 7606 (49.4) | |
| Ethnicity | ||
| White | 6053 (39.3) | |
| Black | 1533 (10.0) | |
| Asian | 5885 (38.2) | |
| Mixed | 989 (6.4) | |
| Other | 674 (4.4) | |
| Unknown | 256 (1.7) | |
| Deprivation decile | ||
| 1: Most deprived | 8260 (53.7) | |
| 2 | 2418 (15.7) | |
| 3 | 1249 (8.1) | |
| 4 | 1190 (7.7) | |
| 5 | 951 (6.2) | |
| 6 | 387 (2.5) | |
| 7 | 341 (2.2) | |
| 8 | 223 (1.5) | |
| 9 | 236 (1.5) | |
| 10: Least deprived | 135 (0.9) | |
| BMI category | Reception | Year 6 |
| Underweight | 235 (1.5) | 264 (1.7) |
| Healthy weight | 11 593 (75.3) | 8887 (57.7) |
| Overweight | 1849 (12.0) | 2353 (15.3) |
| Obese | 1236 (8.0) | 2947 (19.2) |
| Severely obese | 477 (3.1) | 939 (6.1) |
BMIbody mass index
Weight trajectories
Three-quarters of reception (75.3%) and more than half of year 6 (57.7%) children were a healthy weight (table 1). However, the proportion of children in the overweight (including obese and severely obese), obese (including severely obese) and severely obese categories had increased from reception to year 6 from 12.0% to 15.3%, 8.0% to 19.2% and 3.1% to 6.1%, respectively (table 1). Most children who were a healthy weight in reception remained so in year 6 (69.7%) but almost all of the remainder (28.7%) had moved to the overweight, obese or severely obese categories.
A quarter of children in the overweight category in reception remained in it at year 6, with 29.2% moving into the healthy weight category, but 46.3% moving into a higher weight category. Of those in the obese category at reception, nearly half remained in it at year 6 and just over a quarter moved into the severely obese category. Of those in the severely obese category at reception, 68% remained in it at year 6. 30% and 11.7% had their weight increase by ≥1 and ≥2 wt categories between reception and year 6, respectively. Only 7.8% and 0.9% decreased their weight by ≥1 and ≥2 categories, respectively (table 2).
Table 2. Number and proportion of pupils that have stayed in the same or moved BMI weight categories from reception to year 6.
| Year 6 BMI n (%) | |||||||
| Underweight | Healthy weight | Overweight | Obese | Severely obese | Total | ||
| Reception BMIn (%) | Underweight | 75 (31.9) | 143 (60.9) | 10 (4.3) | 5 (2.1) | 2 (0.9) | 235 (100) |
| Healthy weight | 189 (1.6) | 8078 (69.7) | 1683 (14.5) | 1493 (12.9) | 150 (1.3) | 11 593 (100) | |
| Overweight | 0 (0.0) | 539 (29.2) | 454 (24.6) | 718 (38.8) | 138 (7.5) | 1849 (100) | |
| Obese | 0 (0.0) | 120 (9.7) | 194 (15.7) | 596 (48.2) | 326 (26.4) | 1236 (100) | |
| Severely obese | 0 (0.0) | 7 (1.5) | 12 (2.5) | 135 (28.3) | 323 (67.7) | 477 (100) | |
| Total | 264 (1.7) | 8887 (57.8) | 2353 (15.3) | 2947 (19.2) | 939 (6.1) | 15 390 (100) | |
BMIbody mass index
Association between sociodemographic characteristics and weight categories at year 6
Multivariable logistic regression models, adjusted for weight category at reception, estimated that compared with boys, girls in year 6 had 20%, 27% and 36% lower odds of being in the overweight (OR 0.80; 95% CI 0.75 to 0.86; p<0.001), obese (0.73; 95% CI 0.67 to 0.79; p<0.001) or severely obese (0.64; 95% CI 0.55 to 0.75; p<0.001) categories, respectively. Those living in the most deprived decile had higher odds of being in the overweight (1.73; 95% CI 1.13 to 2.65; p<0.05) or obese (2.91; 95% CI 1.55 to 5.47; p<0.001) categories compared with those living in the least deprived decile (table 3).
Table 3. Multivariable logistic regression analysis exploring association between sociodemographic characteristics and weight category in year 6.
| Overweight (including obese and severely obese) at year 6OR (95% CI) | obese (including severely obese) at year 6OR (95% CI) | Severely obese at year 6OR (95% CI) | |
| Reception BMI weight category (healthy weight ref) | |||
| Underweight | 0.169***(0.103 to 0.278) | 0.156***(0.0734 to 0.332) | 0.577(0.142 to 2.349) |
| Overweight | 6.219***(5.576 to 6.937) | 5.429***(4.878 to 6.042) | 6.159***(4.855 to 7.813) |
| Obese | 23.11***(19.05 to 28.03) | 17.99***(15.65 to 20.69) | 27.03***(21.99 to 33.22) |
| Severely obese | 156.7***(74.20 to 331.0) | 138.0***(86.92 to 219.2) | 151.7***(117.7 to 195.4) |
| Sex (male ref) | 0.803***(0.746 to 0.864) | 0.727***(0.667 to 0.792) | 0.641***(0.546 to 0.752) |
| Ethnicity (white ref) | |||
| Black | 1.132(0.991 to 1.294) | 1.176*(1.010 to 1.370) | 1.144(0.876 to 1.494) |
| Asian | 1.290***(1.182 to 1.407) | 1.385***(1.251 to 1.533) | 1.141(0.943 to 1.381) |
| Mixed | 1.250**(1.071 to 1.458) | 1.238*(1.034 to 1.482) | 1.331(0.956 to 1.853) |
| Other | 1.086(0.901 to 1.310) | 0.966(0.769 to 1.213) | 0.829(0.535 to 1.283) |
| Unknown | 0.953(0.707 to 1.284) | 0.922(0.646 to 1.314) | 1.226(0.681 to 2.208) |
| Deprivation decile (least deprived ref) | |||
| Most deprived | 1.734*(1.134 to 2.651) | 2.913***(1.550 to 5.474) | 1.773(0.503 to 6.248) |
| 2 | 1.738*(1.129 to 2.674) | 2.952***(1.562 to 5.581) | 1.943(0.547 to 6.909) |
| 3 | 1.581*(1.019 to 2.454) | 2.517**(1.320 to 4.801) | 1.354(0.373 to 4.912) |
| 4 | 1.404(0.904 to 2.181) | 2.197*(1.150 to 4.197) | 1.086(0.297 to 3.972) |
| 5 | 1.349(0.864 to 2.108) | 2.485**(1.295 to 4.769) | 1.447(0.393 to 5.334) |
| 6 | 1.252(0.772 to 2.030) | 2.174*(1.091 to 4.333) | 0.881(0.213 to 3.642) |
| 7 | 1.087(0.664 to 1.780) | 1.855(0.918 to 3.750) | 0.859(0.199 to 3.720) |
| 8 | 0.966(0.566 to 1.649) | 1.343(0.624 to 2.891) | 0.803(0.159 to 4.055) |
| 9 | 1.074(0.636 to 1.814) | 1.706(0.809 to 3.602) | 0.578(0.102 to 3.283) |
*p<0.05
**p<0.01
***p<0.001
CI95% confidence intervalsORodds ratiorefreference group
Children of Asian ethnicity had greater odds of being in the overweight (1.3 times; 95% CI 1.18 to 1.41; p<0.001) and obese (1.4 times; 95% CI 1.25 to 1.53; p<0.001) categories compared with white children. Mixed ethnicity children also had higher odds of being in the overweight (1.3 times; 95% CI 1.07 to 1.46; p<0.01) and obese (1.2 times; 95% CI 1.03 to 1.48; p<0.05) categories compared with white children. Black children had 1.2 times (95% CI 1.01 to 1.37; p<0.05) higher odds of being in the obese category compared with white children (table 3).
Characteristics of children who experienced rapid weight gain between reception and year 6
Multivariable logistic regression models estimated that compared with boys, girls had 21% and 36% lower odds of moving up ≥1 BMI weight categories (0.79; 95% CI 0.74 to 0.85; p<0.001) or ≥2 wt categories (0.64; 95% CI 0.58 to 0.71; p<0.001), respectively (table 4).
Table 4. Logistic regression models exploring association between sociodemographic characteristics and an increase or decrease of ≥2 or ≥1 BMI weight categories from reception to year 6.
| Increase ≥2 BMI categories | Increase ≥1 BMI categories | |||
| Unadjusted OR (95% CI) | Adjusted OR (95% CI) | Unadjusted OR (95% CI) | Adjusted OR (95% CI) | |
| No. of participants | 15 390 | |||
| Sex (male ref) | 0.65***(0.59 to 0.72) | 0.64***(0.58 to 0.71) | 0.81***(0.75 to 0.87) | 0.79***(0.74 to 0.85) |
| Ethnicity (white ref) | ||||
| Black | 1.17(0.98 to 1.39) | 1.06(0.89 to 1.27) | 1.11(0.98 to 1.26) | 1.02(0.90 to 1.16) |
| Asian | 1.26***(1.12 to 1.41) | 1.18**(1.05 to 1.32) | 1.28***(1.18 to 1.38) | 1.20***(1.10 to 1.30) |
| Mixed | 1.38**(1.13 to 1.69) | 1.31**(1.07 to 1.60) | 1.24**(1.08 to 1.44) | 1.19*(1.03 to 1.38) |
| Other | 0.98(0.75 to 1.27) | 0.93(0.71 to 1.21) | 1.07(0.90 to 1.27) | 1.01(0.84 to 1.20) |
| Unknown | 1.06(0.71 to 1.58) | 0.99(0.66 to 1.48) | 1.06(0.80 to 1.39) | 0.99(0.75 to 1.31) |
| Deprivation decile (least deprived ref) | ||||
| Most deprived | 6.33**(2.01 to 19.92) | 6.06**(1.92 to 19.10) | 2.19***(1.40 to 3.41) | 2.07**(1.32 to 3.23) |
| 2 | 6.28**(1.99 to 19.85) | 6.007**(1.90 to 19.02) | 2.17***(1.38 to 3.39) | 2.04**(1.30 to 3.21) |
| 3 | 5.87**(1.85 to 18.67) | 5.696**(1.79 to 18.14) | 1.947**(1.23 to 3.08) | 1.88**(1.19 to 2.98) |
| 4 | 4.57*(1.43 to 14.59) | 4.41*(1.38 to 14.09) | 1.71*(1.08 to 2.71) | 1.65*(1.04 to 2.61) |
| 5 | 5.29**(1.65 to 16.91) | 5.14**(1.61 to 16.46) | 1.68*(1.05 to 2.67) | 1.62*(1.02 to 2.58) |
| 6 | 4.65*(1.41 to 15.34) | 4.57*(1.38 to 15.08) | 1.57(0.95 to 2.58) | 1.53(0.93 to 2.52) |
| 7 | 3.94*(1.18 to 13.17) | 3.81*(1.14 to 12.76) | 1.42(0.85 to 2.36) | 1.38(0.83 to 2.29) |
| 8 | 2.50(0.69 to 9.03) | 2.46(0.68 to 8.88) | 1.24(0.72 to 2.13) | 1.22(0.71 to 2.11) |
| 9 | 3.20(0.96 to 11.19) | 3.20(0.91 to 11.20) | 1.28(0.74 to 2.19) | 1.27(0.74 to 2.19) |
*p<0.05
**p<0.01
***p<0.001
BMIbody mass indexCI95% confidence intervalsORAdjusted and unadjusted odds ratiorefreference group
Compared with white children, Asian children had higher odds of increasing ≥1 (1.20; 95% CI 1.10 to 1.30; p<0.001) or ≥2 wt categories (1.18; 95% CI 1.05 to 1.32; p<0.01) between reception and year 6. Children of mixed ethnicity also had higher odds of increasing ≥1 (1.19; 95% CI 1.03 to 1.38; p<0.05) and ≥2 wt categories (1.31; 95% CI 1.07 to 1.60; p<0.01) compared with white children.
Compared with those in the least deprived decile, children living in the most deprived decile had 2.1 times (95% CI 1.32 to 3.23; p<0.01) higher odds of moving up ≥1 wt categories, and 6.1 times (95% CI 1.92 to 19.10; p<0.01) higher odds of increasing ≥2 wt categories between reception and year 6.
Regarding children who moved down weight categories between reception and year 6, those of Asian ethnicity had 25% (0.75; 95% CI 0.65 to 0.87; p<0.001) and 37% (0.63; 95% CI 0.42 to 0.94; p<0.05) lower odds of decreasing ≥1 and ≥2 wt categories, respectively, compared with white children.
Discussion
In this study, we found that between reception (age 4–5 years) and year 6 (age 10–11 years), 30% of children had weight category increases, and less than 8% of children decreased their weight category. By year 6, 41% had excess weight with 25% having obesity or severe obesity. Previous studies have shown that children with obesity are 5 times more likely to have obesity as adults, and that 70% of adults with obesity did not have excess weight as children.23 In addition, there is evidence from a 31-year cohort study to suggest that a higher rate of BMI increase in childhood is associated with the development or persistence of obesity in adulthood.24 The study authors highlighted the importance of intervention in young childhood to prevent obesity in adulthood. Given this evidence, our findings suggest that a large proportion of children are at high risk of adult obesity. It is, therefore, important to understand who is most at risk of both excess weight and weight gain in childhood so that early intervention can be appropriately targeted to prevent adult obesity.
Similar to previous studies,11 15 25 we found that boys had greater odds of being at higher weight categories compared with girls by year 6, after adjustment for weight category at reception. Compared with white children, Asian, mixed and black children had higher odds of obesity by year 6, with Asian children having the largest increase in risk. The increased risk of obesity in year 6 for black children was modest in our study (obese: 18%; p<0.05) compared with other studies that have shown a higher risk of weight gain in this ethnic group.11 15 Compared with the white ethnic group, children of mixed ethnicity had the greatest risk of rapid weight gain, followed by Asian children. This is in keeping with previous studies11 14 15 23 that children of ethnicities other than white were more likely to be affected by persistent weight gain.
In this study, we also found that children living in more deprived areas are at higher risk of overweight and obesity at year 6 and of rapid weight gain between reception and year 6. In particular, children living in the most deprived decile were more than six times more likely to increase two or more weight categories between reception and year 6, compared with those living in the least deprived decile. Again, this supports the findings from a previous study that children living in the most deprived areas were not only more likely to enter primary school with higher weights than their counterparts in the least deprived decile but were also more likely to weigh more by the time they leave primary school.14 The link between socioeconomic position and childhood obesity in high-income countries has been well documented, and the proposed mechanisms include poor nutrition in early life, lack of access to healthy food, and adverse local food and physical activity environments.26 Our findings of higher increases in weight gain in children in more deprived areas highlight that these factors are cumulative across childhood.
Study strengths and limitations
This study included a large population of primary school-aged children which was representative of the ethnic, gender and sociodemographic make-up of Birmingham. We used data from four cohorts of the NCMP, which included 99% of state-funded schools with 96% children within the schools undergoing measurements. BMI was calculated from objective height and weight measurements taken by trained professionals. We were able to link measurement data from reception and year 6 for over 15 000 children, enabling longitudinal analysis at the individual level.
A limitation is that private (non-state funded) schools were not included. These children are likely to differ from the children from state-funded schools, particularly in terms of socioeconomic status. Also, IMD was used as a measure of deprivation, but this can be a poor proxy for socioeconomic status as it is a measure of small areas deprivation rather than an individual’s socioeconomic status.
In terms of the data used, it is routinely collected and so there was limited scope for exploring factors associated with rapid weight gain beyond sex, ethnicity and deprivation. For example, early adiposity rebound in children predicts obesity in adolescence,27 but exploration of this was beyond the scope of this study. Also, we did not have access to any data on dietary or physical activity behaviours, or the environmental factors that influence these behaviours and so were unable to explore the relationship between these factors and weight gain across childhood. A further limitation is that it is unclear if the 44% of children who did not have linked data were more likely to have weight gain between reception and year 6. If this was the case, our analyses may have underestimated the proportion of children experiencing rapid weight gain. Finally, this study focused on a single large city in the UK with high ethnic diversity and deprivation. While providing a valuable study population to examine ethnic and socioeconomic differences in childhood weight gain, the specific social and environmental characteristics of the city may limit the generalisability of the findings to other populations.
Conclusion
We found that just under one-third of children had their weight category increase between the ages of 4–5 and 10–11 years. The characteristics associated with rapid weight gain trajectories were male sex, mixed and Asian ethnicity, and high deprivation. Of particular note is the greatly increased risk of a high level of weight gain (ie, an increase of two weight categories) that children experiencing deprivation have, compared with those with low deprivation. This highlights the children who are more likely to have obesity in adulthood and a resulting increased risk of obesity-related chronic disease. Policy-makers and commissioners can use this study to help plan resources to tackle obesity in children in a targeted way to lessen the long-term chronic disease burden and reduce inequalities in health.
Acknowledgements
This research was part of MM’s Master’s in Public Health dissertation with MJP as supervisor. MM cleaned and analysed data and drafted manuscript; MJP reviewed and edited manuscript. MM is grateful to Mohan Singh for data extraction and cleaning and for invaluable advice from James Martin, Albert Uribe and Julia Pauschardt; and to Birmingham City Council for access to the data.
Footnotes
Funding: The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Data availability free text: All local authorities hold data for their own areas. MM no longer has accessed to the data as moved on to another role elsewhere.
Patient consent for publication: Not applicable.
Provenance and peer review: Not commissioned; externally peer reviewed.
Patient and public involvement: Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Ethics approval: This was part of MM’s dissertation and used the NCMP data which is a routinely collected data. Approval was sought and received from Birmingham City Council and the Public Health Governance teams for this research. Moreover, the NCMP Operational Guidance8 states: 'The NCMP Regulations allows for local authorities and those acting on their behalf to process NCMP data for the purposes of research, monitoring, audit, the planning of services or for other public health purposes. Local authorities may also provide the NCMP data to others, such as researchers, provided it is disclosed in a form in which no child can be identified. Local authorities are responsible for ensuring that appropriate processes are in place to manage any such data sharing…'. In adherence to this process, all data were anonymised and held on Council secure servers. MM did not require any further action.
Contributor Information
Muna Mohamed, Email: mam050@alumni.bham.ac.uk.
Miranda J Pallan, Email: M.J.Pallan@bham.ac.uk.
Data availability statement
Data may be obtained from a third party and are not publicly available.
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